Continuous_Control_train.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from unityagents import UnityEnvironment\n",
    "from collections import deque\n",
    "import numpy as np\n",
    "import torch\n",
    "\n",
    "import datetime;\n",
    "\n",
    "import json\n",
    "\n",
    "config = json.load(open('config.json'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:unityagents:\n",
      "'Academy' started successfully!\n",
      "Unity Academy name: Academy\n",
      "        Number of Brains: 1\n",
      "        Number of External Brains : 1\n",
      "        Lesson number : 0\n",
      "        Reset Parameters :\n",
      "\t\tgoal_speed -> 1.0\n",
      "\t\tgoal_size -> 5.0\n",
      "Unity brain name: ReacherBrain\n",
      "        Number of Visual Observations (per agent): 0\n",
      "        Vector Observation space type: continuous\n",
      "        Vector Observation space size (per agent): 33\n",
      "        Number of stacked Vector Observation: 1\n",
      "        Vector Action space type: continuous\n",
      "        Vector Action space size (per agent): 4\n",
      "        Vector Action descriptions: , , , \n"
     ]
    }
   ],
   "source": [
    "env = UnityEnvironment(file_name='Reacher_Windows_x86_64_multi/Reacher.exe',no_graphics=True, seed = config['SEED']['environment'])\n",
    "#,no_graphics=True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get the default brain\n",
    "brain_name = env.brain_names[0]\n",
    "brain = env.brains[brain_name]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of agents: 20\n",
      "Size of each action: 4\n",
      "There are 20 agents. Each observes a state with length: 33\n",
      "The state for the first agent looks like: [ 0.00000000e+00 -4.00000000e+00  0.00000000e+00  1.00000000e+00\n",
      " -0.00000000e+00 -0.00000000e+00 -4.37113883e-08  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00 -1.00000000e+01  0.00000000e+00\n",
      "  1.00000000e+00 -0.00000000e+00 -0.00000000e+00 -4.37113883e-08\n",
      "  0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00\n",
      "  0.00000000e+00  0.00000000e+00  5.58052063e-01 -1.00000000e+00\n",
      " -7.98051453e+00  0.00000000e+00  1.00000000e+00  0.00000000e+00\n",
      "  5.63595533e-01]\n"
     ]
    }
   ],
   "source": [
    "# reset the environment\n",
    "env_info = env.reset(train_mode=True)[brain_name]\n",
    "\n",
    "# number of agents\n",
    "num_agents = len(env_info.agents)\n",
    "print('Number of agents:', num_agents)\n",
    "\n",
    "# size of each action\n",
    "action_size = brain.vector_action_space_size\n",
    "print('Size of each action:', action_size)\n",
    "\n",
    "# examine the state space \n",
    "states = env_info.vector_observations\n",
    "state_size = states.shape[1]\n",
    "print('There are {} agents. Each observes a state with length: {}'.format(states.shape[0], state_size))\n",
    "print('The state for the first agent looks like:', states[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'TAU': 0.001, 'LR_CRITIC': 0.0001, 'LR_ACTOR': 0.0001, 'GAMMA': 0.99, 'BUFFER_SIZE': 400000, 'BATCH_SIZE': 256, 'WEIGHT_DECAY': 0, 'NOISE_SIGMA': 0.1, 'SEED': {'environment': 10, 'agent': 42}, 'NETWORK': {'dropout': 0.2}}\n",
      "Actor(\n",
      "  (fc1): Linear(in_features=33, out_features=256, bias=True)\n",
      "  (batch): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
      "  (fc2): Linear(in_features=256, out_features=128, bias=True)\n",
      "  (fc3): Linear(in_features=128, out_features=4, bias=True)\n",
      ")\n",
      "Critic(\n",
      "  (fc1): Linear(in_features=33, out_features=256, bias=True)\n",
      "  (batch): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
      "  (fc2): Linear(in_features=260, out_features=128, bias=True)\n",
      "  (dropout): Dropout(p=0.2)\n",
      "  (fc3): Linear(in_features=128, out_features=1, bias=True)\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "from agent_ddpg import Agent\n",
    "\n",
    "print(config)\n",
    "agent = Agent(state_size, action_size, config['SEED']['agent'])\n",
    "print(agent.actor_local)\n",
    "print(agent.critic_local)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total score (averaged over agents) this episode\t1:\t0.6525\tAverage Score:\t0.6525\ttime: 0:00:32.499360\n",
      "Total score (averaged over agents) this episode\t2:\t0.9505\tAverage Score:\t0.8015\ttime: 0:00:32.607362\n",
      "Total score (averaged over agents) this episode\t3:\t0.9245\tAverage Score:\t0.8425\ttime: 0:00:32.389336\n",
      "Total score (averaged over agents) this episode\t4:\t0.7280\tAverage Score:\t0.8139\ttime: 0:00:32.295639\n",
      "Total score (averaged over agents) this episode\t5:\t0.3555\tAverage Score:\t0.7222\ttime: 0:00:33.282524\n",
      "Total score (averaged over agents) this episode\t6:\t0.3130\tAverage Score:\t0.6540\ttime: 0:00:33.945194\n",
      "Total score (averaged over agents) this episode\t7:\t0.2075\tAverage Score:\t0.5902\ttime: 0:00:34.473281\n",
      "Total score (averaged over agents) this episode\t8:\t0.1790\tAverage Score:\t0.5388\ttime: 0:00:33.669337\n",
      "Total score (averaged over agents) this episode\t9:\t0.1345\tAverage Score:\t0.4939\ttime: 0:00:32.816918\n",
      "Total score (averaged over agents) this episode\t10:\t0.1705\tAverage Score:\t0.4615\ttime: 0:00:32.825940\n",
      "Total score (averaged over agents) this episode\t11:\t0.3635\tAverage Score:\t0.4526\ttime: 0:00:33.211506\n",
      "Total score (averaged over agents) this episode\t12:\t0.6700\tAverage Score:\t0.4707\ttime: 0:00:35.478566\n",
      "Total score (averaged over agents) this episode\t13:\t0.5935\tAverage Score:\t0.4802\ttime: 0:00:37.208510\n",
      "Total score (averaged over agents) this episode\t14:\t0.7240\tAverage Score:\t0.4976\ttime: 0:00:35.182446\n",
      "Total score (averaged over agents) this episode\t15:\t0.7400\tAverage Score:\t0.5138\ttime: 0:00:34.963913\n",
      "Total score (averaged over agents) this episode\t16:\t0.9485\tAverage Score:\t0.5409\ttime: 0:00:34.474311\n",
      "Total score (averaged over agents) this episode\t17:\t0.8350\tAverage Score:\t0.5582\ttime: 0:00:34.537346\n",
      "Total score (averaged over agents) this episode\t18:\t1.1505\tAverage Score:\t0.5911\ttime: 0:00:34.950899\n",
      "Total score (averaged over agents) this episode\t19:\t0.9725\tAverage Score:\t0.6112\ttime: 0:00:35.156013\n",
      "Total score (averaged over agents) this episode\t20:\t1.4415\tAverage Score:\t0.6527\ttime: 0:00:35.906160\n",
      "Total score (averaged over agents) this episode\t21:\t1.1215\tAverage Score:\t0.6750\ttime: 0:00:35.235975\n",
      "Total score (averaged over agents) this episode\t22:\t1.4000\tAverage Score:\t0.7080\ttime: 0:00:35.634616\n",
      "Total score (averaged over agents) this episode\t23:\t1.1380\tAverage Score:\t0.7267\ttime: 0:00:36.847841\n",
      "Total score (averaged over agents) this episode\t24:\t1.1885\tAverage Score:\t0.7459\ttime: 0:00:35.436998\n",
      "Total score (averaged over agents) this episode\t25:\t1.1940\tAverage Score:\t0.7639\ttime: 0:00:35.512544\n",
      "Total score (averaged over agents) this episode\t26:\t1.0380\tAverage Score:\t0.7744\ttime: 0:00:34.863865\n",
      "Total score (averaged over agents) this episode\t27:\t1.4840\tAverage Score:\t0.8007\ttime: 0:00:35.794608\n",
      "Total score (averaged over agents) this episode\t28:\t1.5300\tAverage Score:\t0.8267\ttime: 0:00:36.903056\n",
      "Total score (averaged over agents) this episode\t29:\t1.1555\tAverage Score:\t0.8381\ttime: 0:00:35.035902\n",
      "Total score (averaged over agents) this episode\t30:\t1.9145\tAverage Score:\t0.8739\ttime: 0:00:35.025394\n",
      "Total score (averaged over agents) this episode\t31:\t1.9335\tAverage Score:\t0.9081\ttime: 0:00:34.988903\n",
      "Total score (averaged over agents) this episode\t32:\t2.9165\tAverage Score:\t0.9709\ttime: 0:00:35.252468\n",
      "Total score (averaged over agents) this episode\t33:\t2.3965\tAverage Score:\t1.0141\ttime: 0:00:35.206975\n",
      "Total score (averaged over agents) this episode\t34:\t2.6935\tAverage Score:\t1.0635\ttime: 0:00:35.111918\n",
      "Total score (averaged over agents) this episode\t35:\t3.3645\tAverage Score:\t1.1292\ttime: 0:00:35.150966\n",
      "Total score (averaged over agents) this episode\t36:\t1.8230\tAverage Score:\t1.1485\ttime: 0:00:35.033936\n",
      "Total score (averaged over agents) this episode\t37:\t2.6480\tAverage Score:\t1.1890\ttime: 0:00:35.042916\n",
      "Total score (averaged over agents) this episode\t38:\t2.7025\tAverage Score:\t1.2289\ttime: 0:00:35.122426\n",
      "Total score (averaged over agents) this episode\t39:\t1.9465\tAverage Score:\t1.2473\ttime: 0:00:35.248967\n",
      "Total score (averaged over agents) this episode\t40:\t2.0185\tAverage Score:\t1.2665\ttime: 0:00:35.236462\n",
      "Total score (averaged over agents) this episode\t41:\t1.6850\tAverage Score:\t1.2767\ttime: 0:00:35.154950\n",
      "Total score (averaged over agents) this episode\t42:\t1.9155\tAverage Score:\t1.2920\ttime: 0:00:35.662583\n",
      "Total score (averaged over agents) this episode\t43:\t2.5315\tAverage Score:\t1.3208\ttime: 0:00:35.189940\n",
      "Total score (averaged over agents) this episode\t44:\t2.3450\tAverage Score:\t1.3441\ttime: 0:00:35.265460\n",
      "Total score (averaged over agents) this episode\t45:\t3.0905\tAverage Score:\t1.3829\ttime: 0:00:35.164928\n",
      "Total score (averaged over agents) this episode\t46:\t3.3145\tAverage Score:\t1.4249\ttime: 0:00:35.149928\n",
      "Total score (averaged over agents) this episode\t47:\t3.7625\tAverage Score:\t1.4746\ttime: 0:00:35.372517\n",
      "Total score (averaged over agents) this episode\t48:\t5.0405\tAverage Score:\t1.5489\ttime: 0:00:35.225951\n",
      "Total score (averaged over agents) this episode\t49:\t3.7435\tAverage Score:\t1.5937\ttime: 0:00:35.229950\n",
      "Total score (averaged over agents) this episode\t50:\t4.3345\tAverage Score:\t1.6485\ttime: 0:00:35.377013\n",
      "Total score (averaged over agents) this episode\t51:\t3.9980\tAverage Score:\t1.6946\ttime: 0:00:35.206470\n",
      "Total score (averaged over agents) this episode\t52:\t3.9340\tAverage Score:\t1.7376\ttime: 0:00:34.562820\n",
      "Total score (averaged over agents) this episode\t53:\t4.0795\tAverage Score:\t1.7818\ttime: 0:00:33.526072\n",
      "Total score (averaged over agents) this episode\t54:\t4.5360\tAverage Score:\t1.8328\ttime: 0:00:33.615119\n",
      "Total score (averaged over agents) this episode\t55:\t3.2370\tAverage Score:\t1.8583\ttime: 0:00:33.531051\n",
      "Total score (averaged over agents) this episode\t56:\t2.8105\tAverage Score:\t1.8753\ttime: 0:00:33.911153\n",
      "Total score (averaged over agents) this episode\t57:\t2.9110\tAverage Score:\t1.8935\ttime: 0:00:34.622337\n",
      "Total score (averaged over agents) this episode\t58:\t2.5765\tAverage Score:\t1.9053\ttime: 0:00:33.712088\n",
      "Total score (averaged over agents) this episode\t59:\t2.9690\tAverage Score:\t1.9233\ttime: 0:00:33.555562\n",
      "Total score (averaged over agents) this episode\t60:\t3.7665\tAverage Score:\t1.9540\ttime: 0:00:34.291162\n",
      "Total score (averaged over agents) this episode\t61:\t3.5825\tAverage Score:\t1.9807\ttime: 0:00:34.564335\n",
      "Total score (averaged over agents) this episode\t62:\t3.8665\tAverage Score:\t2.0112\ttime: 0:00:34.380754\n",
      "Total score (averaged over agents) this episode\t63:\t4.5750\tAverage Score:\t2.0518\ttime: 0:00:34.343249\n",
      "Total score (averaged over agents) this episode\t64:\t4.8625\tAverage Score:\t2.0958\ttime: 0:00:34.373776\n",
      "Total score (averaged over agents) this episode\t65:\t3.7135\tAverage Score:\t2.1207\ttime: 0:00:34.245227\n",
      "Total score (averaged over agents) this episode\t66:\t4.3560\tAverage Score:\t2.1545\ttime: 0:00:33.606609\n",
      "Total score (averaged over agents) this episode\t67:\t3.2420\tAverage Score:\t2.1708\ttime: 0:00:33.629574\n",
      "Total score (averaged over agents) this episode\t68:\t4.1415\tAverage Score:\t2.1997\ttime: 0:00:33.633086\n",
      "Total score (averaged over agents) this episode\t69:\t4.2010\tAverage Score:\t2.2287\ttime: 0:00:33.434037\n",
      "Total score (averaged over agents) this episode\t70:\t3.8050\tAverage Score:\t2.2513\ttime: 0:00:33.453559\n",
      "Total score (averaged over agents) this episode\t71:\t3.6015\tAverage Score:\t2.2703\ttime: 0:00:33.500094\n",
      "Total score (averaged over agents) this episode\t72:\t4.4340\tAverage Score:\t2.3003\ttime: 0:00:33.583080\n",
      "Total score (averaged over agents) this episode\t73:\t4.1270\tAverage Score:\t2.3253\ttime: 0:00:33.621581\n",
      "Total score (averaged over agents) this episode\t74:\t4.6485\tAverage Score:\t2.3567\ttime: 0:00:33.613575\n",
      "Total score (averaged over agents) this episode\t75:\t4.1855\tAverage Score:\t2.3811\ttime: 0:00:33.645574\n",
      "Total score (averaged over agents) this episode\t76:\t4.2300\tAverage Score:\t2.4055\ttime: 0:00:33.554075\n",
      "Total score (averaged over agents) this episode\t77:\t4.2750\tAverage Score:\t2.4297\ttime: 0:00:33.634629\n",
      "Total score (averaged over agents) this episode\t78:\t3.5545\tAverage Score:\t2.4442\ttime: 0:00:33.617076\n",
      "Total score (averaged over agents) this episode\t79:\t3.4650\tAverage Score:\t2.4571\ttime: 0:00:33.745115\n",
      "Total score (averaged over agents) this episode\t80:\t2.6155\tAverage Score:\t2.4591\ttime: 0:00:33.624580\n",
      "Total score (averaged over agents) this episode\t81:\t4.4445\tAverage Score:\t2.4836\ttime: 0:00:33.630588\n",
      "Total score (averaged over agents) this episode\t82:\t4.8980\tAverage Score:\t2.5130\ttime: 0:00:33.586562\n",
      "Total score (averaged over agents) this episode\t83:\t4.9300\tAverage Score:\t2.5421\ttime: 0:00:33.552082\n",
      "Total score (averaged over agents) this episode\t84:\t4.4235\tAverage Score:\t2.5645\ttime: 0:00:33.363061\n",
      "Total score (averaged over agents) this episode\t85:\t4.8125\tAverage Score:\t2.5910\ttime: 0:00:33.362026\n",
      "Total score (averaged over agents) this episode\t86:\t4.3570\tAverage Score:\t2.6115\ttime: 0:00:33.369525\n",
      "Total score (averaged over agents) this episode\t87:\t3.7960\tAverage Score:\t2.6251\ttime: 0:00:33.869015\n",
      "Total score (averaged over agents) this episode\t88:\t4.8020\tAverage Score:\t2.6499\ttime: 0:00:33.404044\n",
      "Total score (averaged over agents) this episode\t89:\t4.4505\tAverage Score:\t2.6701\ttime: 0:00:33.399531\n",
      "Total score (averaged over agents) this episode\t90:\t4.4500\tAverage Score:\t2.6899\ttime: 0:00:33.408072\n",
      "Total score (averaged over agents) this episode\t91:\t4.5795\tAverage Score:\t2.7106\ttime: 0:00:33.480064\n",
      "Total score (averaged over agents) this episode\t92:\t4.6135\tAverage Score:\t2.7313\ttime: 0:00:34.150910\n",
      "Total score (averaged over agents) this episode\t93:\t4.7730\tAverage Score:\t2.7533\ttime: 0:00:33.599576\n",
      "Total score (averaged over agents) this episode\t94:\t4.6000\tAverage Score:\t2.7729\ttime: 0:00:33.439536\n",
      "Total score (averaged over agents) this episode\t95:\t5.3535\tAverage Score:\t2.8001\ttime: 0:00:33.472535\n",
      "Total score (averaged over agents) this episode\t96:\t4.6120\tAverage Score:\t2.8190\ttime: 0:00:33.426536\n",
      "Total score (averaged over agents) this episode\t97:\t4.4640\tAverage Score:\t2.8359\ttime: 0:00:33.536604\n",
      "Total score (averaged over agents) this episode\t98:\t4.4000\tAverage Score:\t2.8519\ttime: 0:00:33.509045\n",
      "Total score (averaged over agents) this episode\t99:\t2.2010\tAverage Score:\t2.8453\ttime: 0:00:33.457543\n",
      "Total score (averaged over agents) this episode\t100:\t2.6125\tAverage Score:\t2.8430\ttime: 0:00:33.437530\n",
      "Episode 100\tAverage Score: 2.84\n",
      "Total score (averaged over agents) this episode\t101:\t3.6390\tAverage Score:\t2.8728\ttime: 0:00:33.559570\n",
      "Total score (averaged over agents) this episode\t102:\t3.8225\tAverage Score:\t2.9016\ttime: 0:00:33.478631\n",
      "Total score (averaged over agents) this episode\t103:\t3.0730\tAverage Score:\t2.9230\ttime: 0:00:33.370064\n",
      "Total score (averaged over agents) this episode\t104:\t3.6130\tAverage Score:\t2.9519\ttime: 0:00:33.347018\n",
      "Total score (averaged over agents) this episode\t105:\t2.6685\tAverage Score:\t2.9750\ttime: 0:00:33.239009\n",
      "Total score (averaged over agents) this episode\t106:\t3.4235\tAverage Score:\t3.0061\ttime: 0:00:33.257502\n",
      "Total score (averaged over agents) this episode\t107:\t3.8355\tAverage Score:\t3.0424\ttime: 0:00:33.230496\n",
      "Total score (averaged over agents) this episode\t108:\t3.4520\tAverage Score:\t3.0751\ttime: 0:00:33.345517\n",
      "Total score (averaged over agents) this episode\t109:\t4.9520\tAverage Score:\t3.1233\ttime: 0:00:33.384069\n",
      "Total score (averaged over agents) this episode\t110:\t4.2360\tAverage Score:\t3.1640\ttime: 0:00:33.811129\n",
      "Total score (averaged over agents) this episode\t111:\t4.2605\tAverage Score:\t3.2029\ttime: 0:00:33.503549\n",
      "Total score (averaged over agents) this episode\t112:\t3.3540\tAverage Score:\t3.2298\ttime: 0:00:33.426047\n",
      "Total score (averaged over agents) this episode\t113:\t4.9390\tAverage Score:\t3.2732\ttime: 0:00:33.450538\n",
      "Total score (averaged over agents) this episode\t114:\t2.6705\tAverage Score:\t3.2927\ttime: 0:00:33.589563\n",
      "Total score (averaged over agents) this episode\t115:\t2.7450\tAverage Score:\t3.3127\ttime: 0:00:33.453541\n",
      "Total score (averaged over agents) this episode\t116:\t2.7020\tAverage Score:\t3.3303\ttime: 0:00:33.421074\n",
      "Total score (averaged over agents) this episode\t117:\t3.1390\tAverage Score:\t3.3533\ttime: 0:00:33.461036\n",
      "Total score (averaged over agents) this episode\t118:\t2.7670\tAverage Score:\t3.3695\ttime: 0:00:33.519548\n",
      "Total score (averaged over agents) this episode\t119:\t3.2965\tAverage Score:\t3.3927\ttime: 0:00:33.531559\n",
      "Total score (averaged over agents) this episode\t120:\t2.5205\tAverage Score:\t3.4035\ttime: 0:00:33.428543\n",
      "Total score (averaged over agents) this episode\t121:\t2.9760\tAverage Score:\t3.4221\ttime: 0:00:33.431544\n",
      "Total score (averaged over agents) this episode\t122:\t2.5785\tAverage Score:\t3.4338\ttime: 0:00:33.508598\n",
      "Total score (averaged over agents) this episode\t123:\t3.0675\tAverage Score:\t3.4531\ttime: 0:00:33.405015\n",
      "Total score (averaged over agents) this episode\t124:\t2.8995\tAverage Score:\t3.4703\ttime: 0:00:33.342036\n",
      "Total score (averaged over agents) this episode\t125:\t2.6415\tAverage Score:\t3.4847\ttime: 0:00:33.335507\n",
      "Total score (averaged over agents) this episode\t126:\t2.5555\tAverage Score:\t3.4999\ttime: 0:00:33.439043\n",
      "Total score (averaged over agents) this episode\t127:\t2.4270\tAverage Score:\t3.5093\ttime: 0:00:33.281490\n",
      "Total score (averaged over agents) this episode\t128:\t3.3180\tAverage Score:\t3.5272\ttime: 0:00:33.362522\n",
      "Total score (averaged over agents) this episode\t129:\t3.2690\tAverage Score:\t3.5483\ttime: 0:00:33.346563\n",
      "Total score (averaged over agents) this episode\t130:\t2.9515\tAverage Score:\t3.5587\ttime: 0:00:33.387018\n",
      "Total score (averaged over agents) this episode\t131:\t3.5255\tAverage Score:\t3.5746\ttime: 0:00:33.411521\n",
      "Total score (averaged over agents) this episode\t132:\t3.5670\tAverage Score:\t3.5811\ttime: 0:00:33.469545\n",
      "Total score (averaged over agents) this episode\t133:\t2.3205\tAverage Score:\t3.5804\ttime: 0:00:33.545565\n",
      "Total score (averaged over agents) this episode\t134:\t2.4605\tAverage Score:\t3.5781\ttime: 0:00:33.500555\n",
      "Total score (averaged over agents) this episode\t135:\t2.8390\tAverage Score:\t3.5728\ttime: 0:00:33.487863\n",
      "Total score (averaged over agents) this episode\t136:\t3.2545\tAverage Score:\t3.5871\ttime: 0:00:33.470247\n",
      "Total score (averaged over agents) this episode\t137:\t2.7455\tAverage Score:\t3.5881\ttime: 0:00:33.629073\n",
      "Total score (averaged over agents) this episode\t138:\t3.6540\tAverage Score:\t3.5976\ttime: 0:00:33.465531\n",
      "Total score (averaged over agents) this episode\t139:\t2.3590\tAverage Score:\t3.6017\ttime: 0:00:33.435537\n",
      "Total score (averaged over agents) this episode\t140:\t3.3580\tAverage Score:\t3.6151\ttime: 0:00:33.512555\n",
      "Total score (averaged over agents) this episode\t141:\t3.6430\tAverage Score:\t3.6347\ttime: 0:00:33.936650\n",
      "Total score (averaged over agents) this episode\t142:\t2.7070\tAverage Score:\t3.6426\ttime: 0:00:33.442527\n",
      "Total score (averaged over agents) this episode\t143:\t3.1155\tAverage Score:\t3.6485\ttime: 0:00:33.414535\n",
      "Total score (averaged over agents) this episode\t144:\t3.7405\tAverage Score:\t3.6624\ttime: 0:00:33.489090\n",
      "Total score (averaged over agents) this episode\t145:\t2.6505\tAverage Score:\t3.6580\ttime: 0:00:33.301995\n",
      "Total score (averaged over agents) this episode\t146:\t2.8400\tAverage Score:\t3.6533\ttime: 0:00:33.341529\n",
      "Total score (averaged over agents) this episode\t147:\t2.7225\tAverage Score:\t3.6429\ttime: 0:00:33.281495\n",
      "Total score (averaged over agents) this episode\t148:\t2.9560\tAverage Score:\t3.6220\ttime: 0:00:33.299499\n",
      "Total score (averaged over agents) this episode\t149:\t2.4730\tAverage Score:\t3.6093\ttime: 0:00:33.390363\n",
      "Total score (averaged over agents) this episode\t150:\t2.6355\tAverage Score:\t3.5923\ttime: 0:00:33.355538\n",
      "Total score (averaged over agents) this episode\t151:\t2.1565\tAverage Score:\t3.5739\ttime: 0:00:33.462084\n",
      "Total score (averaged over agents) this episode\t152:\t2.9825\tAverage Score:\t3.5644\ttime: 0:00:33.446050\n",
      "Total score (averaged over agents) this episode\t153:\t2.6875\tAverage Score:\t3.5505\ttime: 0:00:33.518574\n",
      "Total score (averaged over agents) this episode\t154:\t2.2995\tAverage Score:\t3.5281\ttime: 0:00:33.565578\n",
      "Total score (averaged over agents) this episode\t155:\t2.4025\tAverage Score:\t3.5198\ttime: 0:00:33.537573\n",
      "Total score (averaged over agents) this episode\t156:\t1.8240\tAverage Score:\t3.5099\ttime: 0:00:33.503550\n",
      "Total score (averaged over agents) this episode\t157:\t2.2410\tAverage Score:\t3.5032\ttime: 0:00:33.529554\n",
      "Total score (averaged over agents) this episode\t158:\t2.3560\tAverage Score:\t3.5010\ttime: 0:00:33.527099\n",
      "Total score (averaged over agents) this episode\t159:\t3.0270\tAverage Score:\t3.5016\ttime: 0:00:33.481041\n",
      "Total score (averaged over agents) this episode\t160:\t2.6790\tAverage Score:\t3.4907\ttime: 0:00:33.495576\n",
      "Total score (averaged over agents) this episode\t161:\t3.0265\tAverage Score:\t3.4851\ttime: 0:00:33.507561\n",
      "Total score (averaged over agents) this episode\t162:\t2.1595\tAverage Score:\t3.4681\ttime: 0:00:33.502061\n",
      "Total score (averaged over agents) this episode\t163:\t2.2770\tAverage Score:\t3.4451\ttime: 0:00:33.476547\n",
      "Total score (averaged over agents) this episode\t164:\t2.6200\tAverage Score:\t3.4227\ttime: 0:00:33.424075\n",
      "Total score (averaged over agents) this episode\t165:\t1.5200\tAverage Score:\t3.4007\ttime: 0:00:33.340012\n",
      "Total score (averaged over agents) this episode\t166:\t1.7715\tAverage Score:\t3.3749\ttime: 0:00:33.360510\n",
      "Total score (averaged over agents) this episode\t167:\t1.7820\tAverage Score:\t3.3603\ttime: 0:00:33.342515\n",
      "Total score (averaged over agents) this episode\t168:\t2.1990\tAverage Score:\t3.3409\ttime: 0:00:33.498557\n",
      "Total score (averaged over agents) this episode\t169:\t1.7450\tAverage Score:\t3.3163\ttime: 0:00:33.426535\n",
      "Total score (averaged over agents) this episode\t170:\t2.5230\tAverage Score:\t3.3035\ttime: 0:00:33.414072\n",
      "Total score (averaged over agents) this episode\t171:\t2.3600\tAverage Score:\t3.2911\ttime: 0:00:33.435021\n",
      "Total score (averaged over agents) this episode\t172:\t2.1800\tAverage Score:\t3.2685\ttime: 0:00:33.549573\n",
      "Total score (averaged over agents) this episode\t173:\t2.4630\tAverage Score:\t3.2519\ttime: 0:00:33.681102\n",
      "Total score (averaged over agents) this episode\t174:\t1.8200\tAverage Score:\t3.2236\ttime: 0:00:33.572565\n",
      "Total score (averaged over agents) this episode\t175:\t3.0330\tAverage Score:\t3.2121\ttime: 0:00:33.520561\n",
      "Total score (averaged over agents) this episode\t176:\t2.5040\tAverage Score:\t3.1948\ttime: 0:00:33.612527\n",
      "Total score (averaged over agents) this episode\t177:\t1.9060\tAverage Score:\t3.1711\ttime: 0:00:33.562166\n",
      "Total score (averaged over agents) this episode\t178:\t2.3665\tAverage Score:\t3.1592\ttime: 0:00:33.566141\n",
      "Total score (averaged over agents) this episode\t179:\t2.2205\tAverage Score:\t3.1468\ttime: 0:00:33.605568\n",
      "Total score (averaged over agents) this episode\t180:\t2.1320\tAverage Score:\t3.1420\ttime: 0:00:33.549571\n",
      "Total score (averaged over agents) this episode\t181:\t2.2410\tAverage Score:\t3.1199\ttime: 0:00:33.479547\n",
      "Total score (averaged over agents) this episode\t182:\t1.9230\tAverage Score:\t3.0902\ttime: 0:00:33.534555\n",
      "Total score (averaged over agents) this episode\t183:\t1.5780\tAverage Score:\t3.0567\ttime: 0:00:33.466085\n",
      "Total score (averaged over agents) this episode\t184:\t2.6830\tAverage Score:\t3.0393\ttime: 0:00:33.428025\n",
      "Total score (averaged over agents) this episode\t185:\t1.5970\tAverage Score:\t3.0071\ttime: 0:00:33.422527\n",
      "Total score (averaged over agents) this episode\t186:\t1.6840\tAverage Score:\t2.9804\ttime: 0:00:33.323515\n",
      "Total score (averaged over agents) this episode\t187:\t1.7475\tAverage Score:\t2.9599\ttime: 0:00:33.382528\n",
      "Total score (averaged over agents) this episode\t188:\t1.2280\tAverage Score:\t2.9241\ttime: 0:00:33.353527\n",
      "Total score (averaged over agents) this episode\t189:\t1.5090\tAverage Score:\t2.8947\ttime: 0:00:33.388068\n",
      "Total score (averaged over agents) this episode\t190:\t1.8055\tAverage Score:\t2.8683\ttime: 0:00:33.491041\n",
      "Total score (averaged over agents) this episode\t191:\t1.9635\tAverage Score:\t2.8421\ttime: 0:00:33.573581\n",
      "Total score (averaged over agents) this episode\t192:\t2.0175\tAverage Score:\t2.8162\ttime: 0:00:33.525072\n",
      "Total score (averaged over agents) this episode\t193:\t2.6005\tAverage Score:\t2.7944\ttime: 0:00:33.551561\n",
      "Total score (averaged over agents) this episode\t194:\t1.9985\tAverage Score:\t2.7684\ttime: 0:00:33.527565\n",
      "Total score (averaged over agents) this episode\t195:\t2.5185\tAverage Score:\t2.7401\ttime: 0:00:33.766127\n",
      "Total score (averaged over agents) this episode\t196:\t2.1350\tAverage Score:\t2.7153\ttime: 0:00:33.563069\n",
      "Total score (averaged over agents) this episode\t197:\t3.9780\tAverage Score:\t2.7104\ttime: 0:00:33.533100\n",
      "Total score (averaged over agents) this episode\t198:\t2.4525\tAverage Score:\t2.6910\ttime: 0:00:33.552060\n",
      "Total score (averaged over agents) this episode\t199:\t2.7070\tAverage Score:\t2.6960\ttime: 0:00:33.542567\n",
      "Total score (averaged over agents) this episode\t200:\t3.3995\tAverage Score:\t2.7039\ttime: 0:00:33.530547\n",
      "Episode 200\tAverage Score: 2.70\n",
      "Total score (averaged over agents) this episode\t201:\t3.6850\tAverage Score:\t2.7044\ttime: 0:00:33.488542\n",
      "Total score (averaged over agents) this episode\t202:\t3.3510\tAverage Score:\t2.6996\ttime: 0:00:33.465536\n",
      "Total score (averaged over agents) this episode\t203:\t3.3455\tAverage Score:\t2.7024\ttime: 0:00:33.427582\n",
      "Total score (averaged over agents) this episode\t204:\t3.3230\tAverage Score:\t2.6995\ttime: 0:00:33.316003\n",
      "Total score (averaged over agents) this episode\t205:\t4.1255\tAverage Score:\t2.7140\ttime: 0:00:33.332005\n",
      "Total score (averaged over agents) this episode\t206:\t3.8250\tAverage Score:\t2.7181\ttime: 0:00:33.411530\n",
      "Total score (averaged over agents) this episode\t207:\t5.1240\tAverage Score:\t2.7309\ttime: 0:00:33.387018\n",
      "Total score (averaged over agents) this episode\t208:\t5.4060\tAverage Score:\t2.7505\ttime: 0:00:33.395522\n",
      "Total score (averaged over agents) this episode\t209:\t5.4185\tAverage Score:\t2.7551\ttime: 0:00:33.506052\n",
      "Total score (averaged over agents) this episode\t210:\t3.6675\tAverage Score:\t2.7495\ttime: 0:00:33.471591\n",
      "Total score (averaged over agents) this episode\t211:\t5.0320\tAverage Score:\t2.7572\ttime: 0:00:33.501889\n",
      "Total score (averaged over agents) this episode\t212:\t4.8145\tAverage Score:\t2.7718\ttime: 0:00:33.498321\n",
      "Total score (averaged over agents) this episode\t213:\t4.8570\tAverage Score:\t2.7710\ttime: 0:00:33.607569\n",
      "Total score (averaged over agents) this episode\t214:\t4.4730\tAverage Score:\t2.7890\ttime: 0:00:33.548546\n",
      "Total score (averaged over agents) this episode\t215:\t3.8440\tAverage Score:\t2.8000\ttime: 0:00:33.511553\n",
      "Total score (averaged over agents) this episode\t216:\t3.6100\tAverage Score:\t2.8091\ttime: 0:00:33.637073\n",
      "Total score (averaged over agents) this episode\t217:\t3.9735\tAverage Score:\t2.8174\ttime: 0:00:33.547104\n",
      "Total score (averaged over agents) this episode\t218:\t4.1350\tAverage Score:\t2.8311\ttime: 0:00:33.576061\n",
      "Total score (averaged over agents) this episode\t219:\t4.6780\tAverage Score:\t2.8449\ttime: 0:00:33.484051\n",
      "Total score (averaged over agents) this episode\t220:\t5.9700\tAverage Score:\t2.8794\ttime: 0:00:33.529561\n",
      "Total score (averaged over agents) this episode\t221:\t4.9880\tAverage Score:\t2.8995\ttime: 0:00:33.523572\n",
      "Total score (averaged over agents) this episode\t222:\t5.3355\tAverage Score:\t2.9271\ttime: 0:00:33.677579\n",
      "Total score (averaged over agents) this episode\t223:\t6.1215\tAverage Score:\t2.9576\ttime: 0:00:33.442528\n",
      "Total score (averaged over agents) this episode\t224:\t7.4370\tAverage Score:\t3.0030\ttime: 0:00:33.463083\n",
      "Total score (averaged over agents) this episode\t225:\t8.3855\tAverage Score:\t3.0604\ttime: 0:00:33.865129\n",
      "Total score (averaged over agents) this episode\t226:\t7.1930\tAverage Score:\t3.1068\ttime: 0:00:33.491538\n",
      "Total score (averaged over agents) this episode\t227:\t7.2230\tAverage Score:\t3.1548\ttime: 0:00:34.151208\n",
      "Total score (averaged over agents) this episode\t228:\t7.5630\tAverage Score:\t3.1972\ttime: 0:00:33.598596\n",
      "Total score (averaged over agents) this episode\t229:\t8.1270\tAverage Score:\t3.2458\ttime: 0:00:33.329505\n",
      "Total score (averaged over agents) this episode\t230:\t7.0895\tAverage Score:\t3.2872\ttime: 0:00:33.333054\n",
      "Total score (averaged over agents) this episode\t231:\t7.7285\tAverage Score:\t3.3292\ttime: 0:00:33.608065\n",
      "Total score (averaged over agents) this episode\t232:\t5.5170\tAverage Score:\t3.3487\ttime: 0:00:33.505553\n",
      "Total score (averaged over agents) this episode\t233:\t5.7715\tAverage Score:\t3.3832\ttime: 0:00:33.499550\n",
      "Total score (averaged over agents) this episode\t234:\t5.8905\tAverage Score:\t3.4175\ttime: 0:00:33.522558\n",
      "Total score (averaged over agents) this episode\t235:\t5.3810\tAverage Score:\t3.4429\ttime: 0:00:33.543570\n",
      "Total score (averaged over agents) this episode\t236:\t7.0545\tAverage Score:\t3.4809\ttime: 0:00:33.526098\n",
      "Total score (averaged over agents) this episode\t237:\t7.4825\tAverage Score:\t3.5283\ttime: 0:00:33.538052\n",
      "Total score (averaged over agents) this episode\t238:\t6.2245\tAverage Score:\t3.5540\ttime: 0:00:33.497556\n",
      "Total score (averaged over agents) this episode\t239:\t7.0555\tAverage Score:\t3.6010\ttime: 0:00:33.522803\n",
      "Total score (averaged over agents) this episode\t240:\t6.6530\tAverage Score:\t3.6339\ttime: 0:00:33.487555\n",
      "Total score (averaged over agents) this episode\t241:\t5.4305\tAverage Score:\t3.6518\ttime: 0:00:33.502056\n",
      "Total score (averaged over agents) this episode\t242:\t7.7085\tAverage Score:\t3.7018\ttime: 0:00:33.574555\n",
      "Total score (averaged over agents) this episode\t243:\t6.6515\tAverage Score:\t3.7372\ttime: 0:00:33.464493\n",
      "Total score (averaged over agents) this episode\t244:\t6.1375\tAverage Score:\t3.7612\ttime: 0:00:33.463137\n",
      "Total score (averaged over agents) this episode\t245:\t6.5645\tAverage Score:\t3.8003\ttime: 0:00:33.372117\n",
      "Total score (averaged over agents) this episode\t246:\t7.2500\tAverage Score:\t3.8444\ttime: 0:00:33.307512\n",
      "Total score (averaged over agents) this episode\t247:\t7.7875\tAverage Score:\t3.8950\ttime: 0:00:33.421534\n",
      "Total score (averaged over agents) this episode\t248:\t7.0065\tAverage Score:\t3.9355\ttime: 0:00:33.339889\n",
      "Total score (averaged over agents) this episode\t249:\t5.8980\tAverage Score:\t3.9698\ttime: 0:00:33.587075\n",
      "Total score (averaged over agents) this episode\t250:\t7.7255\tAverage Score:\t4.0207\ttime: 0:00:33.436078\n",
      "Total score (averaged over agents) this episode\t251:\t6.4500\tAverage Score:\t4.0636\ttime: 0:00:33.434023\n",
      "Total score (averaged over agents) this episode\t252:\t7.0220\tAverage Score:\t4.1040\ttime: 0:00:33.522577\n",
      "Total score (averaged over agents) this episode\t253:\t5.6440\tAverage Score:\t4.1336\ttime: 0:00:33.611076\n",
      "Total score (averaged over agents) this episode\t254:\t6.2350\tAverage Score:\t4.1729\ttime: 0:00:33.548574\n",
      "Total score (averaged over agents) this episode\t255:\t6.5200\tAverage Score:\t4.2141\ttime: 0:00:33.556560\n",
      "Total score (averaged over agents) this episode\t256:\t6.3965\tAverage Score:\t4.2598\ttime: 0:00:33.591798\n",
      "Total score (averaged over agents) this episode\t257:\t6.9545\tAverage Score:\t4.3070\ttime: 0:00:33.563613\n",
      "Total score (averaged over agents) this episode\t258:\t7.1670\tAverage Score:\t4.3551\ttime: 0:00:33.538041\n",
      "Total score (averaged over agents) this episode\t259:\t7.7330\tAverage Score:\t4.4022\ttime: 0:00:33.538567\n",
      "Total score (averaged over agents) this episode\t260:\t7.1920\tAverage Score:\t4.4473\ttime: 0:00:33.613611\n",
      "Total score (averaged over agents) this episode\t261:\t7.7730\tAverage Score:\t4.4947\ttime: 0:00:33.573562\n",
      "Total score (averaged over agents) this episode\t262:\t6.4025\tAverage Score:\t4.5372\ttime: 0:00:33.555064\n",
      "Total score (averaged over agents) this episode\t263:\t9.2040\tAverage Score:\t4.6064\ttime: 0:00:33.489551\n",
      "Total score (averaged over agents) this episode\t264:\t8.3680\tAverage Score:\t4.6639\ttime: 0:00:33.391067\n",
      "Total score (averaged over agents) this episode\t265:\t7.2185\tAverage Score:\t4.7209\ttime: 0:00:33.331003\n",
      "Total score (averaged over agents) this episode\t266:\t8.0060\tAverage Score:\t4.7833\ttime: 0:00:33.337601\n",
      "Total score (averaged over agents) this episode\t267:\t8.2055\tAverage Score:\t4.8475\ttime: 0:00:33.390521\n",
      "Total score (averaged over agents) this episode\t268:\t6.7620\tAverage Score:\t4.8931\ttime: 0:00:33.317510\n",
      "Total score (averaged over agents) this episode\t269:\t7.5355\tAverage Score:\t4.9510\ttime: 0:00:33.441553\n",
      "Total score (averaged over agents) this episode\t270:\t7.0320\tAverage Score:\t4.9961\ttime: 0:00:33.416073\n",
      "Total score (averaged over agents) this episode\t271:\t8.2075\tAverage Score:\t5.0546\ttime: 0:00:33.536816\n",
      "Total score (averaged over agents) this episode\t272:\t6.6755\tAverage Score:\t5.0995\ttime: 0:00:33.497047\n",
      "Total score (averaged over agents) this episode\t273:\t6.3940\tAverage Score:\t5.1389\ttime: 0:00:33.590570\n",
      "Total score (averaged over agents) this episode\t274:\t5.9185\tAverage Score:\t5.1798\ttime: 0:00:33.571563\n",
      "Total score (averaged over agents) this episode\t275:\t6.7410\tAverage Score:\t5.2169\ttime: 0:00:33.510554\n",
      "Total score (averaged over agents) this episode\t276:\t7.9755\tAverage Score:\t5.2716\ttime: 0:00:33.686585\n",
      "Total score (averaged over agents) this episode\t277:\t8.0285\tAverage Score:\t5.3329\ttime: 0:00:33.533100\n",
      "Total score (averaged over agents) this episode\t278:\t9.2085\tAverage Score:\t5.4013\ttime: 0:00:33.543053\n",
      "Total score (averaged over agents) this episode\t279:\t8.3220\tAverage Score:\t5.4623\ttime: 0:00:33.603573\n",
      "Total score (averaged over agents) this episode\t280:\t9.0255\tAverage Score:\t5.5312\ttime: 0:00:33.832134\n",
      "Total score (averaged over agents) this episode\t281:\t9.9090\tAverage Score:\t5.6079\ttime: 0:00:33.602588\n",
      "Total score (averaged over agents) this episode\t282:\t8.2355\tAverage Score:\t5.6710\ttime: 0:00:33.594570\n",
      "Total score (averaged over agents) this episode\t283:\t7.8580\tAverage Score:\t5.7338\ttime: 0:00:33.478775\n",
      "Total score (averaged over agents) this episode\t284:\t8.2445\tAverage Score:\t5.7895\ttime: 0:00:33.333340\n",
      "Total score (averaged over agents) this episode\t285:\t8.2555\tAverage Score:\t5.8560\ttime: 0:00:33.372013\n",
      "Total score (averaged over agents) this episode\t286:\t8.5740\tAverage Score:\t5.9249\ttime: 0:00:33.436553\n",
      "Total score (averaged over agents) this episode\t287:\t7.9050\tAverage Score:\t5.9865\ttime: 0:00:33.356518\n",
      "Total score (averaged over agents) this episode\t288:\t7.3280\tAverage Score:\t6.0475\ttime: 0:00:33.410542\n",
      "Total score (averaged over agents) this episode\t289:\t6.7700\tAverage Score:\t6.1001\ttime: 0:00:33.458536\n",
      "Total score (averaged over agents) this episode\t290:\t8.5140\tAverage Score:\t6.1672\ttime: 0:00:33.456083\n",
      "Total score (averaged over agents) this episode\t291:\t8.2910\tAverage Score:\t6.2305\ttime: 0:00:33.478048\n",
      "Total score (averaged over agents) this episode\t292:\t10.2120\tAverage Score:\t6.3124\ttime: 0:00:33.546910\n",
      "Total score (averaged over agents) this episode\t293:\t7.6630\tAverage Score:\t6.3631\ttime: 0:00:33.585077\n",
      "Total score (averaged over agents) this episode\t294:\t8.8940\tAverage Score:\t6.4320\ttime: 0:00:33.557061\n",
      "Total score (averaged over agents) this episode\t295:\t8.2785\tAverage Score:\t6.4896\ttime: 0:00:33.499053\n",
      "Total score (averaged over agents) this episode\t296:\t8.0560\tAverage Score:\t6.5488\ttime: 0:00:33.517564\n",
      "Total score (averaged over agents) this episode\t297:\t9.0890\tAverage Score:\t6.5999\ttime: 0:00:33.621573\n",
      "Total score (averaged over agents) this episode\t298:\t8.6175\tAverage Score:\t6.6616\ttime: 0:00:33.712141\n",
      "Total score (averaged over agents) this episode\t299:\t7.2455\tAverage Score:\t6.7070\ttime: 0:00:33.572062\n",
      "Total score (averaged over agents) this episode\t300:\t9.0435\tAverage Score:\t6.7634\ttime: 0:00:33.536565\n",
      "Episode 300\tAverage Score: 6.76\n",
      "Total score (averaged over agents) this episode\t301:\t9.6930\tAverage Score:\t6.8235\ttime: 0:00:33.551065\n",
      "Total score (averaged over agents) this episode\t302:\t8.0695\tAverage Score:\t6.8707\ttime: 0:00:33.524555\n",
      "Total score (averaged over agents) this episode\t303:\t8.6695\tAverage Score:\t6.9239\ttime: 0:00:33.662088\n",
      "Total score (averaged over agents) this episode\t304:\t9.7800\tAverage Score:\t6.9885\ttime: 0:00:33.434045\n",
      "Total score (averaged over agents) this episode\t305:\t8.5285\tAverage Score:\t7.0325\ttime: 0:00:33.363061\n",
      "Total score (averaged over agents) this episode\t306:\t8.6685\tAverage Score:\t7.0809\ttime: 0:00:33.381014\n",
      "Total score (averaged over agents) this episode\t307:\t8.2020\tAverage Score:\t7.1117\ttime: 0:00:33.402043\n",
      "Total score (averaged over agents) this episode\t308:\t8.1910\tAverage Score:\t7.1396\ttime: 0:00:33.447051\n",
      "Total score (averaged over agents) this episode\t309:\t8.3635\tAverage Score:\t7.1690\ttime: 0:00:33.386020\n",
      "Total score (averaged over agents) this episode\t310:\t10.0475\tAverage Score:\t7.2328\ttime: 0:00:33.455040\n",
      "Total score (averaged over agents) this episode\t311:\t7.5000\tAverage Score:\t7.2575\ttime: 0:00:33.436582\n",
      "Total score (averaged over agents) this episode\t312:\t9.3065\tAverage Score:\t7.3024\ttime: 0:00:33.521097\n",
      "Total score (averaged over agents) this episode\t313:\t9.0060\tAverage Score:\t7.3439\ttime: 0:00:33.626091\n",
      "Total score (averaged over agents) this episode\t314:\t7.6890\tAverage Score:\t7.3761\ttime: 0:00:33.618573\n",
      "Total score (averaged over agents) this episode\t315:\t9.1610\tAverage Score:\t7.4292\ttime: 0:00:33.540557\n",
      "Total score (averaged over agents) this episode\t316:\t8.9065\tAverage Score:\t7.4822\ttime: 0:00:33.579568\n",
      "Total score (averaged over agents) this episode\t317:\t9.0145\tAverage Score:\t7.5326\ttime: 0:00:33.598590\n",
      "Total score (averaged over agents) this episode\t318:\t12.0935\tAverage Score:\t7.6122\ttime: 0:00:33.557075\n",
      "Total score (averaged over agents) this episode\t319:\t9.5330\tAverage Score:\t7.6608\ttime: 0:00:33.524098\n",
      "Total score (averaged over agents) this episode\t320:\t10.0460\tAverage Score:\t7.7015\ttime: 0:00:33.523063\n",
      "Total score (averaged over agents) this episode\t321:\t8.5695\tAverage Score:\t7.7373\ttime: 0:00:33.581563\n",
      "Total score (averaged over agents) this episode\t322:\t8.9170\tAverage Score:\t7.7731\ttime: 0:00:33.498050\n",
      "Total score (averaged over agents) this episode\t323:\t8.9190\tAverage Score:\t7.8011\ttime: 0:00:33.483550\n",
      "Total score (averaged over agents) this episode\t324:\t8.8925\tAverage Score:\t7.8157\ttime: 0:00:33.370026\n",
      "Total score (averaged over agents) this episode\t325:\t9.6030\tAverage Score:\t7.8278\ttime: 0:00:33.433077\n",
      "Total score (averaged over agents) this episode\t326:\t8.5710\tAverage Score:\t7.8416\ttime: 0:00:33.407025\n",
      "Total score (averaged over agents) this episode\t327:\t8.4970\tAverage Score:\t7.8544\ttime: 0:00:33.358509\n",
      "Total score (averaged over agents) this episode\t328:\t9.2610\tAverage Score:\t7.8713\ttime: 0:00:33.402524\n",
      "Total score (averaged over agents) this episode\t329:\t8.7260\tAverage Score:\t7.8773\ttime: 0:00:33.407522\n",
      "Total score (averaged over agents) this episode\t330:\t7.7710\tAverage Score:\t7.8842\ttime: 0:00:33.687607\n",
      "Total score (averaged over agents) this episode\t331:\t9.9055\tAverage Score:\t7.9059\ttime: 0:00:33.454082\n",
      "Total score (averaged over agents) this episode\t332:\t9.4425\tAverage Score:\t7.9452\ttime: 0:00:33.567059\n",
      "Total score (averaged over agents) this episode\t333:\t8.1630\tAverage Score:\t7.9691\ttime: 0:00:33.568560\n",
      "Total score (averaged over agents) this episode\t334:\t8.8590\tAverage Score:\t7.9988\ttime: 0:00:33.726837\n",
      "Total score (averaged over agents) this episode\t335:\t8.9535\tAverage Score:\t8.0345\ttime: 0:00:33.594569\n",
      "Total score (averaged over agents) this episode\t336:\t9.2660\tAverage Score:\t8.0566\ttime: 0:00:33.528057\n",
      "Total score (averaged over agents) this episode\t337:\t8.8740\tAverage Score:\t8.0705\ttime: 0:00:33.564706\n",
      "Total score (averaged over agents) this episode\t338:\t10.2145\tAverage Score:\t8.1104\ttime: 0:00:33.484550\n",
      "Total score (averaged over agents) this episode\t339:\t10.0650\tAverage Score:\t8.1405\ttime: 0:00:33.563107\n",
      "Total score (averaged over agents) this episode\t340:\t9.3585\tAverage Score:\t8.1676\ttime: 0:00:33.543053\n",
      "Total score (averaged over agents) this episode\t341:\t9.9835\tAverage Score:\t8.2131\ttime: 0:00:33.549562\n",
      "Total score (averaged over agents) this episode\t342:\t9.4060\tAverage Score:\t8.2301\ttime: 0:00:33.523559\n",
      "Total score (averaged over agents) this episode\t343:\t8.9895\tAverage Score:\t8.2535\ttime: 0:00:33.540571\n",
      "Total score (averaged over agents) this episode\t344:\t9.6115\tAverage Score:\t8.2882\ttime: 0:00:33.432540\n",
      "Total score (averaged over agents) this episode\t345:\t10.3065\tAverage Score:\t8.3256\ttime: 0:00:33.369567\n",
      "Total score (averaged over agents) this episode\t346:\t9.8710\tAverage Score:\t8.3518\ttime: 0:00:33.352009\n",
      "Total score (averaged over agents) this episode\t347:\t10.4615\tAverage Score:\t8.3786\ttime: 0:00:33.366531\n",
      "Total score (averaged over agents) this episode\t348:\t10.5795\tAverage Score:\t8.4143\ttime: 0:00:33.373041\n",
      "Total score (averaged over agents) this episode\t349:\t10.8850\tAverage Score:\t8.4642\ttime: 0:00:33.506566\n",
      "Total score (averaged over agents) this episode\t350:\t11.0125\tAverage Score:\t8.4970\ttime: 0:00:33.650084\n",
      "Total score (averaged over agents) this episode\t351:\t10.3480\tAverage Score:\t8.5360\ttime: 0:00:33.545058\n",
      "Total score (averaged over agents) this episode\t352:\t10.8705\tAverage Score:\t8.5745\ttime: 0:00:33.593068\n",
      "Total score (averaged over agents) this episode\t353:\t9.7800\tAverage Score:\t8.6159\ttime: 0:00:33.608118\n",
      "Total score (averaged over agents) this episode\t354:\t10.4355\tAverage Score:\t8.6579\ttime: 0:00:33.573068\n",
      "Total score (averaged over agents) this episode\t355:\t10.5770\tAverage Score:\t8.6984\ttime: 0:00:33.562592\n",
      "Total score (averaged over agents) this episode\t356:\t9.7975\tAverage Score:\t8.7325\ttime: 0:00:33.526551\n",
      "Total score (averaged over agents) this episode\t357:\t10.5330\tAverage Score:\t8.7682\ttime: 0:00:33.822135\n",
      "Total score (averaged over agents) this episode\t358:\t9.4860\tAverage Score:\t8.7914\ttime: 0:00:33.577578\n",
      "Total score (averaged over agents) this episode\t359:\t9.0345\tAverage Score:\t8.8044\ttime: 0:00:33.542103\n",
      "Total score (averaged over agents) this episode\t360:\t8.6350\tAverage Score:\t8.8189\ttime: 0:00:33.554063\n",
      "Total score (averaged over agents) this episode\t361:\t10.2040\tAverage Score:\t8.8432\ttime: 0:00:33.611576\n",
      "Total score (averaged over agents) this episode\t362:\t10.2510\tAverage Score:\t8.8817\ttime: 0:00:33.622092\n",
      "Total score (averaged over agents) this episode\t363:\t10.7580\tAverage Score:\t8.8972\ttime: 0:00:33.490634\n",
      "Total score (averaged over agents) this episode\t364:\t8.3760\tAverage Score:\t8.8973\ttime: 0:00:33.518550\n",
      "Total score (averaged over agents) this episode\t365:\t10.6090\tAverage Score:\t8.9312\ttime: 0:00:33.411542\n",
      "Total score (averaged over agents) this episode\t366:\t8.8240\tAverage Score:\t8.9394\ttime: 0:00:33.360061\n",
      "Total score (averaged over agents) this episode\t367:\t10.1040\tAverage Score:\t8.9584\ttime: 0:00:33.425026\n",
      "Total score (averaged over agents) this episode\t368:\t9.1640\tAverage Score:\t8.9824\ttime: 0:00:33.479568\n",
      "Total score (averaged over agents) this episode\t369:\t7.8215\tAverage Score:\t8.9852\ttime: 0:00:33.421521\n",
      "Total score (averaged over agents) this episode\t370:\t8.5325\tAverage Score:\t9.0002\ttime: 0:00:33.528552\n",
      "Total score (averaged over agents) this episode\t371:\t6.6150\tAverage Score:\t8.9843\ttime: 0:00:33.495559\n",
      "Total score (averaged over agents) this episode\t372:\t7.1575\tAverage Score:\t8.9891\ttime: 0:00:33.550354\n",
      "Total score (averaged over agents) this episode\t373:\t8.7405\tAverage Score:\t9.0126\ttime: 0:00:33.582110\n",
      "Total score (averaged over agents) this episode\t374:\t7.2365\tAverage Score:\t9.0258\ttime: 0:00:33.596072\n",
      "Total score (averaged over agents) this episode\t375:\t8.3775\tAverage Score:\t9.0422\ttime: 0:00:33.568582\n",
      "Total score (averaged over agents) this episode\t376:\t9.3815\tAverage Score:\t9.0562\ttime: 0:00:33.554565\n",
      "Total score (averaged over agents) this episode\t377:\t8.8435\tAverage Score:\t9.0644\ttime: 0:00:33.623095\n",
      "Total score (averaged over agents) this episode\t378:\t8.8770\tAverage Score:\t9.0610\ttime: 0:00:33.563582\n",
      "Total score (averaged over agents) this episode\t379:\t10.0685\tAverage Score:\t9.0785\ttime: 0:00:33.624577\n",
      "Total score (averaged over agents) this episode\t380:\t10.4800\tAverage Score:\t9.0931\ttime: 0:00:33.539102\n",
      "Total score (averaged over agents) this episode\t381:\t9.8940\tAverage Score:\t9.0929\ttime: 0:00:33.551047\n",
      "Total score (averaged over agents) this episode\t382:\t8.6400\tAverage Score:\t9.0970\ttime: 0:00:33.573067\n",
      "Total score (averaged over agents) this episode\t383:\t9.3375\tAverage Score:\t9.1117\ttime: 0:00:33.560573\n",
      "Total score (averaged over agents) this episode\t384:\t9.5530\tAverage Score:\t9.1248\ttime: 0:00:33.610087\n",
      "Total score (averaged over agents) this episode\t385:\t10.1210\tAverage Score:\t9.1435\ttime: 0:00:33.411543\n",
      "Total score (averaged over agents) this episode\t386:\t8.1740\tAverage Score:\t9.1395\ttime: 0:00:33.449524\n",
      "Total score (averaged over agents) this episode\t387:\t8.3070\tAverage Score:\t9.1435\ttime: 0:00:33.342057\n",
      "Total score (averaged over agents) this episode\t388:\t10.2515\tAverage Score:\t9.1727\ttime: 0:00:33.496070\n",
      "Total score (averaged over agents) this episode\t389:\t10.2710\tAverage Score:\t9.2078\ttime: 0:00:33.467048\n",
      "Total score (averaged over agents) this episode\t390:\t11.5450\tAverage Score:\t9.2381\ttime: 0:00:33.517562\n",
      "Total score (averaged over agents) this episode\t391:\t11.3135\tAverage Score:\t9.2683\ttime: 0:00:33.497558\n",
      "Total score (averaged over agents) this episode\t392:\t10.4035\tAverage Score:\t9.2702\ttime: 0:00:33.542555\n",
      "Total score (averaged over agents) this episode\t393:\t9.9340\tAverage Score:\t9.2929\ttime: 0:00:33.644255\n",
      "Total score (averaged over agents) this episode\t394:\t10.9775\tAverage Score:\t9.3137\ttime: 0:00:33.664432\n",
      "Total score (averaged over agents) this episode\t395:\t10.8415\tAverage Score:\t9.3394\ttime: 0:00:33.593076\n",
      "Total score (averaged over agents) this episode\t396:\t9.9295\tAverage Score:\t9.3581\ttime: 0:00:33.585576\n",
      "Total score (averaged over agents) this episode\t397:\t9.9965\tAverage Score:\t9.3672\ttime: 0:00:33.653752\n",
      "Total score (averaged over agents) this episode\t398:\t11.0130\tAverage Score:\t9.3911\ttime: 0:00:33.552562\n",
      "Total score (averaged over agents) this episode\t399:\t11.1710\tAverage Score:\t9.4304\ttime: 0:00:33.548564\n",
      "Total score (averaged over agents) this episode\t400:\t10.9110\tAverage Score:\t9.4491\ttime: 0:00:33.529099\n",
      "Episode 400\tAverage Score: 9.45\n",
      "Total score (averaged over agents) this episode\t401:\t11.1315\tAverage Score:\t9.4635\ttime: 0:00:33.701084\n",
      "Total score (averaged over agents) this episode\t402:\t11.9620\tAverage Score:\t9.5024\ttime: 0:00:33.551572\n",
      "Total score (averaged over agents) this episode\t403:\t10.9630\tAverage Score:\t9.5253\ttime: 0:00:33.546553\n",
      "Total score (averaged over agents) this episode\t404:\t11.3960\tAverage Score:\t9.5415\ttime: 0:00:33.480543\n",
      "Total score (averaged over agents) this episode\t405:\t12.7135\tAverage Score:\t9.5833\ttime: 0:00:33.398527\n",
      "Total score (averaged over agents) this episode\t406:\t11.9910\tAverage Score:\t9.6166\ttime: 0:00:33.451083\n",
      "Total score (averaged over agents) this episode\t407:\t10.8580\tAverage Score:\t9.6431\ttime: 0:00:33.362010\n",
      "Total score (averaged over agents) this episode\t408:\t12.3470\tAverage Score:\t9.6847\ttime: 0:00:33.435536\n",
      "Total score (averaged over agents) this episode\t409:\t11.6825\tAverage Score:\t9.7179\ttime: 0:00:33.395545\n",
      "Total score (averaged over agents) this episode\t410:\t11.3525\tAverage Score:\t9.7309\ttime: 0:00:33.526543\n",
      "Total score (averaged over agents) this episode\t411:\t11.5330\tAverage Score:\t9.7712\ttime: 0:00:33.911650\n",
      "Total score (averaged over agents) this episode\t412:\t10.1425\tAverage Score:\t9.7796\ttime: 0:00:34.431304\n",
      "Total score (averaged over agents) this episode\t413:\t11.4885\tAverage Score:\t9.8044\ttime: 0:00:34.352251\n",
      "Total score (averaged over agents) this episode\t414:\t10.5515\tAverage Score:\t9.8331\ttime: 0:00:34.603792\n",
      "Total score (averaged over agents) this episode\t415:\t10.8595\tAverage Score:\t9.8500\ttime: 0:00:34.304723\n",
      "Total score (averaged over agents) this episode\t416:\t9.7470\tAverage Score:\t9.8584\ttime: 0:00:33.576069\n",
      "Total score (averaged over agents) this episode\t417:\t10.7230\tAverage Score:\t9.8755\ttime: 0:00:33.625597\n",
      "Total score (averaged over agents) this episode\t418:\t12.3280\tAverage Score:\t9.8779\ttime: 0:00:33.550568\n",
      "Total score (averaged over agents) this episode\t419:\t11.9725\tAverage Score:\t9.9023\ttime: 0:00:33.567107\n",
      "Total score (averaged over agents) this episode\t420:\t10.7325\tAverage Score:\t9.9091\ttime: 0:00:33.503045\n",
      "Total score (averaged over agents) this episode\t421:\t11.4330\tAverage Score:\t9.9378\ttime: 0:00:33.558564\n",
      "Total score (averaged over agents) this episode\t422:\t12.4975\tAverage Score:\t9.9736\ttime: 0:00:33.581570\n",
      "Total score (averaged over agents) this episode\t423:\t11.9865\tAverage Score:\t10.0042\ttime: 0:00:33.561583\n",
      "Total score (averaged over agents) this episode\t424:\t12.3450\tAverage Score:\t10.0388\ttime: 0:00:33.397514\n",
      "Total score (averaged over agents) this episode\t425:\t12.8560\tAverage Score:\t10.0713\ttime: 0:00:33.383066\n",
      "Total score (averaged over agents) this episode\t426:\t11.9955\tAverage Score:\t10.1055\ttime: 0:00:33.403044\n",
      "Total score (averaged over agents) this episode\t427:\t10.8110\tAverage Score:\t10.1287\ttime: 0:00:33.346028\n",
      "Total score (averaged over agents) this episode\t428:\t11.0315\tAverage Score:\t10.1464\ttime: 0:00:33.368537\n",
      "Total score (averaged over agents) this episode\t429:\t11.0975\tAverage Score:\t10.1701\ttime: 0:00:33.450551\n",
      "Total score (averaged over agents) this episode\t430:\t11.9740\tAverage Score:\t10.2121\ttime: 0:00:33.437532\n",
      "Total score (averaged over agents) this episode\t431:\t12.0465\tAverage Score:\t10.2335\ttime: 0:00:33.508668\n",
      "Total score (averaged over agents) this episode\t432:\t10.0280\tAverage Score:\t10.2394\ttime: 0:00:33.538102\n",
      "Total score (averaged over agents) this episode\t433:\t9.9605\tAverage Score:\t10.2574\ttime: 0:00:33.659092\n",
      "Total score (averaged over agents) this episode\t434:\t10.9145\tAverage Score:\t10.2779\ttime: 0:00:33.572086\n",
      "Total score (averaged over agents) this episode\t435:\t10.4195\tAverage Score:\t10.2926\ttime: 0:00:33.598563\n",
      "Total score (averaged over agents) this episode\t436:\t11.5090\tAverage Score:\t10.3150\ttime: 0:00:33.623568\n",
      "Total score (averaged over agents) this episode\t437:\t12.9825\tAverage Score:\t10.3561\ttime: 0:00:33.833621\n",
      "Total score (averaged over agents) this episode\t438:\t11.2885\tAverage Score:\t10.3668\ttime: 0:00:33.574109\n",
      "Total score (averaged over agents) this episode\t439:\t10.7770\tAverage Score:\t10.3740\ttime: 0:00:33.622066\n",
      "Total score (averaged over agents) this episode\t440:\t10.1890\tAverage Score:\t10.3823\ttime: 0:00:33.867145\n",
      "Total score (averaged over agents) this episode\t441:\t11.3370\tAverage Score:\t10.3958\ttime: 0:00:33.737117\n",
      "Total score (averaged over agents) this episode\t442:\t11.5885\tAverage Score:\t10.4176\ttime: 0:00:33.637591\n",
      "Total score (averaged over agents) this episode\t443:\t11.0580\tAverage Score:\t10.4383\ttime: 0:00:33.507551\n",
      "Total score (averaged over agents) this episode\t444:\t10.6145\tAverage Score:\t10.4483\ttime: 0:00:33.482554\n",
      "Total score (averaged over agents) this episode\t445:\t10.9360\tAverage Score:\t10.4546\ttime: 0:00:33.360514\n",
      "Total score (averaged over agents) this episode\t446:\t11.7050\tAverage Score:\t10.4730\ttime: 0:00:33.353059\n",
      "Total score (averaged over agents) this episode\t447:\t10.3445\tAverage Score:\t10.4718\ttime: 0:00:33.496049\n",
      "Total score (averaged over agents) this episode\t448:\t11.3230\tAverage Score:\t10.4792\ttime: 0:00:33.390512\n",
      "Total score (averaged over agents) this episode\t449:\t10.7845\tAverage Score:\t10.4782\ttime: 0:00:33.499565\n",
      "Total score (averaged over agents) this episode\t450:\t11.1620\tAverage Score:\t10.4797\ttime: 0:00:33.470571\n",
      "Total score (averaged over agents) this episode\t451:\t11.0850\tAverage Score:\t10.4871\ttime: 0:00:33.568567\n",
      "Total score (averaged over agents) this episode\t452:\t12.5125\tAverage Score:\t10.5035\ttime: 0:00:33.682588\n",
      "Total score (averaged over agents) this episode\t453:\t12.2420\tAverage Score:\t10.5281\ttime: 0:00:33.580111\n",
      "Total score (averaged over agents) this episode\t454:\t13.3000\tAverage Score:\t10.5568\ttime: 0:00:33.652092\n",
      "Total score (averaged over agents) this episode\t455:\t13.0055\tAverage Score:\t10.5811\ttime: 0:00:33.584571\n",
      "Total score (averaged over agents) this episode\t456:\t11.8310\tAverage Score:\t10.6014\ttime: 0:00:33.612579\n",
      "Total score (averaged over agents) this episode\t457:\t12.9950\tAverage Score:\t10.6260\ttime: 0:00:33.652574\n",
      "Total score (averaged over agents) this episode\t458:\t12.6765\tAverage Score:\t10.6579\ttime: 0:00:33.681103\n",
      "Total score (averaged over agents) this episode\t459:\t14.1725\tAverage Score:\t10.7093\ttime: 0:00:33.664605\n",
      "Total score (averaged over agents) this episode\t460:\t13.2580\tAverage Score:\t10.7555\ttime: 0:00:33.588112\n",
      "Total score (averaged over agents) this episode\t461:\t12.9930\tAverage Score:\t10.7834\ttime: 0:00:33.550058\n",
      "Total score (averaged over agents) this episode\t462:\t13.8975\tAverage Score:\t10.8199\ttime: 0:00:33.629077\n",
      "Total score (averaged over agents) this episode\t463:\t12.9525\tAverage Score:\t10.8418\ttime: 0:00:33.486553\n",
      "Total score (averaged over agents) this episode\t464:\t13.1840\tAverage Score:\t10.8899\ttime: 0:00:33.674601\n",
      "Total score (averaged over agents) this episode\t465:\t12.6990\tAverage Score:\t10.9108\ttime: 0:00:33.438535\n",
      "Total score (averaged over agents) this episode\t466:\t12.6235\tAverage Score:\t10.9488\ttime: 0:00:33.406531\n",
      "Total score (averaged over agents) this episode\t467:\t12.6655\tAverage Score:\t10.9744\ttime: 0:00:33.362061\n",
      "Total score (averaged over agents) this episode\t468:\t12.8605\tAverage Score:\t11.0114\ttime: 0:00:33.420026\n",
      "Total score (averaged over agents) this episode\t469:\t13.3240\tAverage Score:\t11.0664\ttime: 0:00:33.434526\n",
      "Total score (averaged over agents) this episode\t470:\t11.3130\tAverage Score:\t11.0942\ttime: 0:00:33.449543\n",
      "Total score (averaged over agents) this episode\t471:\t12.1920\tAverage Score:\t11.1500\ttime: 0:00:33.687615\n",
      "Total score (averaged over agents) this episode\t472:\t11.9100\tAverage Score:\t11.1975\ttime: 0:00:33.557559\n",
      "Total score (averaged over agents) this episode\t473:\t12.5030\tAverage Score:\t11.2352\ttime: 0:00:33.636123\n",
      "Total score (averaged over agents) this episode\t474:\t12.6580\tAverage Score:\t11.2894\ttime: 0:00:33.623071\n",
      "Total score (averaged over agents) this episode\t475:\t12.0375\tAverage Score:\t11.3260\ttime: 0:00:33.616585\n",
      "Total score (averaged over agents) this episode\t476:\t12.5170\tAverage Score:\t11.3573\ttime: 0:00:33.614073\n",
      "Total score (averaged over agents) this episode\t477:\t11.9405\tAverage Score:\t11.3883\ttime: 0:00:33.626569\n",
      "Total score (averaged over agents) this episode\t478:\t11.5700\tAverage Score:\t11.4152\ttime: 0:00:33.563554\n",
      "Total score (averaged over agents) this episode\t479:\t11.6105\tAverage Score:\t11.4306\ttime: 0:00:33.587114\n",
      "Total score (averaged over agents) this episode\t480:\t7.3735\tAverage Score:\t11.3996\ttime: 0:00:33.613065\n",
      "Total score (averaged over agents) this episode\t481:\t1.5035\tAverage Score:\t11.3157\ttime: 0:00:33.533577\n",
      "Total score (averaged over agents) this episode\t482:\t0.5950\tAverage Score:\t11.2352\ttime: 0:00:33.545562\n",
      "Total score (averaged over agents) this episode\t483:\t2.6580\tAverage Score:\t11.1684\ttime: 0:00:33.517553\n",
      "Total score (averaged over agents) this episode\t484:\t6.8735\tAverage Score:\t11.1416\ttime: 0:00:33.458550\n",
      "Total score (averaged over agents) this episode\t485:\t7.3840\tAverage Score:\t11.1143\ttime: 0:00:33.416525\n",
      "Total score (averaged over agents) this episode\t486:\t7.0225\tAverage Score:\t11.1027\ttime: 0:00:33.433077\n",
      "Total score (averaged over agents) this episode\t487:\t7.6025\tAverage Score:\t11.0957\ttime: 0:00:33.453031\n",
      "Total score (averaged over agents) this episode\t488:\t6.9080\tAverage Score:\t11.0623\ttime: 0:00:33.386523\n",
      "Total score (averaged over agents) this episode\t489:\t7.9520\tAverage Score:\t11.0391\ttime: 0:00:33.459543\n",
      "Total score (averaged over agents) this episode\t490:\t7.2850\tAverage Score:\t10.9965\ttime: 0:00:33.511559\n",
      "Total score (averaged over agents) this episode\t491:\t6.6820\tAverage Score:\t10.9502\ttime: 0:00:33.738037\n",
      "Total score (averaged over agents) this episode\t492:\t6.0755\tAverage Score:\t10.9069\ttime: 0:00:33.554556\n",
      "Total score (averaged over agents) this episode\t493:\t6.7425\tAverage Score:\t10.8750\ttime: 0:00:33.636123\n",
      "Total score (averaged over agents) this episode\t494:\t10.2915\tAverage Score:\t10.8681\ttime: 0:00:33.641067\n",
      "Total score (averaged over agents) this episode\t495:\t9.0150\tAverage Score:\t10.8498\ttime: 0:00:33.684589\n",
      "Total score (averaged over agents) this episode\t496:\t9.2445\tAverage Score:\t10.8430\ttime: 0:00:33.600580\n",
      "Total score (averaged over agents) this episode\t497:\t10.1910\tAverage Score:\t10.8449\ttime: 0:00:33.622578\n",
      "Total score (averaged over agents) this episode\t498:\t8.8795\tAverage Score:\t10.8236\ttime: 0:00:33.638604\n",
      "Total score (averaged over agents) this episode\t499:\t8.6470\tAverage Score:\t10.7984\ttime: 0:00:33.602075\n",
      "Total score (averaged over agents) this episode\t500:\t10.1575\tAverage Score:\t10.7908\ttime: 0:00:33.554104\n",
      "Episode 500\tAverage Score: 10.79\n",
      "Total score (averaged over agents) this episode\t501:\t8.7125\tAverage Score:\t10.7666\ttime: 0:00:33.646589\n",
      "Total score (averaged over agents) this episode\t502:\t9.5840\tAverage Score:\t10.7429\ttime: 0:00:33.553049\n",
      "Total score (averaged over agents) this episode\t503:\t9.0870\tAverage Score:\t10.7241\ttime: 0:00:33.677594\n",
      "Total score (averaged over agents) this episode\t504:\t8.5175\tAverage Score:\t10.6953\ttime: 0:00:33.513558\n",
      "Total score (averaged over agents) this episode\t505:\t10.9375\tAverage Score:\t10.6776\ttime: 0:00:33.402528\n",
      "Total score (averaged over agents) this episode\t506:\t9.8800\tAverage Score:\t10.6564\ttime: 0:00:33.372526\n",
      "Total score (averaged over agents) this episode\t507:\t12.5260\tAverage Score:\t10.6731\ttime: 0:00:33.367062\n",
      "Total score (averaged over agents) this episode\t508:\t12.1485\tAverage Score:\t10.6711\ttime: 0:00:33.400024\n",
      "Total score (averaged over agents) this episode\t509:\t10.7170\tAverage Score:\t10.6615\ttime: 0:00:33.407523\n",
      "Total score (averaged over agents) this episode\t510:\t11.6720\tAverage Score:\t10.6647\ttime: 0:00:33.472538\n",
      "Total score (averaged over agents) this episode\t511:\t12.0570\tAverage Score:\t10.6699\ttime: 0:00:33.532549\n",
      "Total score (averaged over agents) this episode\t512:\t12.3445\tAverage Score:\t10.6919\ttime: 0:00:33.554562\n",
      "Total score (averaged over agents) this episode\t513:\t11.5160\tAverage Score:\t10.6922\ttime: 0:00:33.660129\n",
      "Total score (averaged over agents) this episode\t514:\t11.8345\tAverage Score:\t10.7050\ttime: 0:00:33.606074\n",
      "Total score (averaged over agents) this episode\t515:\t11.0100\tAverage Score:\t10.7065\ttime: 0:00:33.570568\n",
      "Total score (averaged over agents) this episode\t516:\t12.6925\tAverage Score:\t10.7360\ttime: 0:00:33.608572\n",
      "Total score (averaged over agents) this episode\t517:\t11.8395\tAverage Score:\t10.7472\ttime: 0:00:33.588593\n",
      "Total score (averaged over agents) this episode\t518:\t9.8735\tAverage Score:\t10.7226\ttime: 0:00:33.745606\n",
      "Total score (averaged over agents) this episode\t519:\t10.4335\tAverage Score:\t10.7072\ttime: 0:00:33.579064\n",
      "Total score (averaged over agents) this episode\t520:\t10.8155\tAverage Score:\t10.7081\ttime: 0:00:33.506543\n",
      "Total score (averaged over agents) this episode\t521:\t10.9545\tAverage Score:\t10.7033\ttime: 0:00:33.515098\n",
      "Total score (averaged over agents) this episode\t522:\t10.1295\tAverage Score:\t10.6796\ttime: 0:00:33.580059\n",
      "Total score (averaged over agents) this episode\t523:\t12.8095\tAverage Score:\t10.6878\ttime: 0:00:33.504553\n",
      "Total score (averaged over agents) this episode\t524:\t10.8555\tAverage Score:\t10.6729\ttime: 0:00:33.426528\n",
      "Total score (averaged over agents) this episode\t525:\t12.1315\tAverage Score:\t10.6657\ttime: 0:00:33.404541\n",
      "Total score (averaged over agents) this episode\t526:\t12.2030\tAverage Score:\t10.6678\ttime: 0:00:33.353015\n",
      "Total score (averaged over agents) this episode\t527:\t11.9930\tAverage Score:\t10.6796\ttime: 0:00:33.368527\n",
      "Total score (averaged over agents) this episode\t528:\t11.6805\tAverage Score:\t10.6861\ttime: 0:00:33.425075\n",
      "Total score (averaged over agents) this episode\t529:\t12.1340\tAverage Score:\t10.6964\ttime: 0:00:33.488044\n",
      "Total score (averaged over agents) this episode\t530:\t13.0085\tAverage Score:\t10.7068\ttime: 0:00:33.481553\n",
      "Total score (averaged over agents) this episode\t531:\t12.3320\tAverage Score:\t10.7096\ttime: 0:00:33.539567\n",
      "Total score (averaged over agents) this episode\t532:\t12.0895\tAverage Score:\t10.7303\ttime: 0:00:33.473549\n",
      "Total score (averaged over agents) this episode\t533:\t11.6815\tAverage Score:\t10.7475\ttime: 0:00:33.573558\n",
      "Total score (averaged over agents) this episode\t534:\t10.9815\tAverage Score:\t10.7481\ttime: 0:00:33.627122\n",
      "Total score (averaged over agents) this episode\t535:\t12.7680\tAverage Score:\t10.7716\ttime: 0:00:33.518057\n",
      "Total score (averaged over agents) this episode\t536:\t13.1695\tAverage Score:\t10.7882\ttime: 0:00:33.528559\n",
      "Total score (averaged over agents) this episode\t537:\t12.0180\tAverage Score:\t10.7786\ttime: 0:00:33.611594\n",
      "Total score (averaged over agents) this episode\t538:\t11.5790\tAverage Score:\t10.7815\ttime: 0:00:33.531562\n",
      "Total score (averaged over agents) this episode\t539:\t10.9095\tAverage Score:\t10.7828\ttime: 0:00:33.524562\n",
      "Total score (averaged over agents) this episode\t540:\t10.7995\tAverage Score:\t10.7889\ttime: 0:00:33.548520\n",
      "Total score (averaged over agents) this episode\t541:\t11.1940\tAverage Score:\t10.7875\ttime: 0:00:33.554113\n",
      "Total score (averaged over agents) this episode\t542:\t11.8740\tAverage Score:\t10.7903\ttime: 0:00:33.558048\n",
      "Total score (averaged over agents) this episode\t543:\t11.0475\tAverage Score:\t10.7902\ttime: 0:00:33.488558\n",
      "Total score (averaged over agents) this episode\t544:\t11.9495\tAverage Score:\t10.8036\ttime: 0:00:33.444532\n",
      "Total score (averaged over agents) this episode\t545:\t10.0855\tAverage Score:\t10.7951\ttime: 0:00:33.548071\n",
      "Total score (averaged over agents) this episode\t546:\t10.2700\tAverage Score:\t10.7807\ttime: 0:00:33.383035\n",
      "Total score (averaged over agents) this episode\t547:\t11.2105\tAverage Score:\t10.7894\ttime: 0:00:33.435039\n",
      "Total score (averaged over agents) this episode\t548:\t12.1315\tAverage Score:\t10.7975\ttime: 0:00:33.463084\n",
      "Total score (averaged over agents) this episode\t549:\t10.5275\tAverage Score:\t10.7949\ttime: 0:00:33.456042\n",
      "Total score (averaged over agents) this episode\t550:\t11.6020\tAverage Score:\t10.7993\ttime: 0:00:33.454546\n",
      "Total score (averaged over agents) this episode\t551:\t10.5460\tAverage Score:\t10.7939\ttime: 0:00:33.486553\n",
      "Total score (averaged over agents) this episode\t552:\t11.8295\tAverage Score:\t10.7871\ttime: 0:00:33.542550\n",
      "Total score (averaged over agents) this episode\t553:\t10.7405\tAverage Score:\t10.7721\ttime: 0:00:33.531558\n",
      "Total score (averaged over agents) this episode\t554:\t8.3950\tAverage Score:\t10.7230\ttime: 0:00:33.529100\n",
      "Total score (averaged over agents) this episode\t555:\t0.7080\tAverage Score:\t10.6000\ttime: 0:00:33.773116\n",
      "Total score (averaged over agents) this episode\t556:\t0.3305\tAverage Score:\t10.4850\ttime: 0:00:33.536551\n",
      "Total score (averaged over agents) this episode\t557:\t4.0125\tAverage Score:\t10.3952\ttime: 0:00:33.618092\n",
      "Total score (averaged over agents) this episode\t558:\t5.6115\tAverage Score:\t10.3246\ttime: 0:00:33.596073\n",
      "Total score (averaged over agents) this episode\t559:\t6.6265\tAverage Score:\t10.2491\ttime: 0:00:33.599584\n",
      "Total score (averaged over agents) this episode\t560:\t8.2685\tAverage Score:\t10.1992\ttime: 0:00:33.542557\n",
      "Total score (averaged over agents) this episode\t561:\t8.8720\tAverage Score:\t10.1580\ttime: 0:00:33.552104\n",
      "Total score (averaged over agents) this episode\t562:\t5.9925\tAverage Score:\t10.0789\ttime: 0:00:33.537538\n",
      "Total score (averaged over agents) this episode\t563:\t7.6015\tAverage Score:\t10.0254\ttime: 0:00:33.533059\n",
      "Total score (averaged over agents) this episode\t564:\t9.7930\tAverage Score:\t9.9915\ttime: 0:00:33.457041\n",
      "Total score (averaged over agents) this episode\t565:\t8.9900\tAverage Score:\t9.9544\ttime: 0:00:33.402527\n",
      "Total score (averaged over agents) this episode\t566:\t8.9205\tAverage Score:\t9.9174\ttime: 0:00:33.498211\n",
      "Total score (averaged over agents) this episode\t567:\t10.3310\tAverage Score:\t9.8941\ttime: 0:00:33.413037\n",
      "Total score (averaged over agents) this episode\t568:\t9.4400\tAverage Score:\t9.8599\ttime: 0:00:33.385037\n",
      "Total score (averaged over agents) this episode\t569:\t10.7000\tAverage Score:\t9.8336\ttime: 0:00:33.445058\n",
      "Total score (averaged over agents) this episode\t570:\t9.3730\tAverage Score:\t9.8142\ttime: 0:00:33.512599\n",
      "Total score (averaged over agents) this episode\t571:\t9.1015\tAverage Score:\t9.7833\ttime: 0:00:33.502051\n",
      "Total score (averaged over agents) this episode\t572:\t10.1105\tAverage Score:\t9.7653\ttime: 0:00:33.730127\n",
      "Total score (averaged over agents) this episode\t573:\t9.5075\tAverage Score:\t9.7354\ttime: 0:00:34.580848\n",
      "Total score (averaged over agents) this episode\t574:\t10.7145\tAverage Score:\t9.7159\ttime: 0:00:34.360277\n",
      "Total score (averaged over agents) this episode\t575:\t10.9290\tAverage Score:\t9.7048\ttime: 0:00:34.227731\n",
      "Total score (averaged over agents) this episode\t576:\t9.7905\tAverage Score:\t9.6776\ttime: 0:00:34.171742\n",
      "Total score (averaged over agents) this episode\t577:\t8.7550\tAverage Score:\t9.6457\ttime: 0:00:34.418766\n",
      "Total score (averaged over agents) this episode\t578:\t9.5695\tAverage Score:\t9.6257\ttime: 0:00:33.823662\n",
      "Total score (averaged over agents) this episode\t579:\t9.0820\tAverage Score:\t9.6004\ttime: 0:00:33.568561\n",
      "Total score (averaged over agents) this episode\t580:\t9.6555\tAverage Score:\t9.6233\ttime: 0:00:33.656128\n",
      "Total score (averaged over agents) this episode\t581:\t11.0460\tAverage Score:\t9.7187\ttime: 0:00:33.537048\n",
      "Total score (averaged over agents) this episode\t582:\t10.8945\tAverage Score:\t9.8217\ttime: 0:00:33.573578\n",
      "Total score (averaged over agents) this episode\t583:\t9.6260\tAverage Score:\t9.8914\ttime: 0:00:33.530553\n",
      "Total score (averaged over agents) this episode\t584:\t10.9400\tAverage Score:\t9.9320\ttime: 0:00:33.576071\n",
      "Total score (averaged over agents) this episode\t585:\t10.7705\tAverage Score:\t9.9659\ttime: 0:00:33.389793\n",
      "Total score (averaged over agents) this episode\t586:\t11.6795\tAverage Score:\t10.0125\ttime: 0:00:33.364525\n",
      "Total score (averaged over agents) this episode\t587:\t11.0730\tAverage Score:\t10.0472\ttime: 0:00:33.382066\n",
      "Total score (averaged over agents) this episode\t588:\t11.6110\tAverage Score:\t10.0942\ttime: 0:00:33.408027\n",
      "Total score (averaged over agents) this episode\t589:\t11.7430\tAverage Score:\t10.1321\ttime: 0:00:33.475543\n",
      "Total score (averaged over agents) this episode\t590:\t10.9485\tAverage Score:\t10.1687\ttime: 0:00:33.425539\n",
      "Total score (averaged over agents) this episode\t591:\t12.7055\tAverage Score:\t10.2290\ttime: 0:00:33.466543\n",
      "Total score (averaged over agents) this episode\t592:\t9.9140\tAverage Score:\t10.2674\ttime: 0:00:33.489552\n",
      "Total score (averaged over agents) this episode\t593:\t10.0190\tAverage Score:\t10.3001\ttime: 0:00:33.640124\n",
      "Total score (averaged over agents) this episode\t594:\t11.5000\tAverage Score:\t10.3122\ttime: 0:00:33.551060\n",
      "Total score (averaged over agents) this episode\t595:\t11.0675\tAverage Score:\t10.3327\ttime: 0:00:33.572800\n",
      "Total score (averaged over agents) this episode\t596:\t10.9865\tAverage Score:\t10.3501\ttime: 0:00:33.611563\n",
      "Total score (averaged over agents) this episode\t597:\t9.7135\tAverage Score:\t10.3454\ttime: 0:00:33.576584\n",
      "Total score (averaged over agents) this episode\t598:\t10.4155\tAverage Score:\t10.3607\ttime: 0:00:33.573567\n",
      "Total score (averaged over agents) this episode\t599:\t9.5760\tAverage Score:\t10.3700\ttime: 0:00:33.778155\n",
      "Total score (averaged over agents) this episode\t600:\t9.8230\tAverage Score:\t10.3667\ttime: 0:00:33.524070\n",
      "Episode 600\tAverage Score: 10.37\n",
      "Total score (averaged over agents) this episode\t601:\t10.7985\tAverage Score:\t10.3875\ttime: 0:00:33.603569\n",
      "Total score (averaged over agents) this episode\t602:\t12.8175\tAverage Score:\t10.4199\ttime: 0:00:33.633575\n",
      "Total score (averaged over agents) this episode\t603:\t11.7550\tAverage Score:\t10.4466\ttime: 0:00:33.633587\n",
      "Total score (averaged over agents) this episode\t604:\t15.0020\tAverage Score:\t10.5114\ttime: 0:00:33.420541\n",
      "Total score (averaged over agents) this episode\t605:\t13.9955\tAverage Score:\t10.5420\ttime: 0:00:33.442549\n",
      "Total score (averaged over agents) this episode\t606:\t13.4265\tAverage Score:\t10.5774\ttime: 0:00:33.476087\n",
      "Total score (averaged over agents) this episode\t607:\t12.9600\tAverage Score:\t10.5818\ttime: 0:00:33.367030\n",
      "Total score (averaged over agents) this episode\t608:\t13.7115\tAverage Score:\t10.5974\ttime: 0:00:33.447063\n",
      "Total score (averaged over agents) this episode\t609:\t10.7020\tAverage Score:\t10.5973\ttime: 0:00:33.510557\n",
      "Total score (averaged over agents) this episode\t610:\t10.1980\tAverage Score:\t10.5825\ttime: 0:00:33.490557\n",
      "Total score (averaged over agents) this episode\t611:\t12.2585\tAverage Score:\t10.5845\ttime: 0:00:33.590576\n",
      "Total score (averaged over agents) this episode\t612:\t11.7170\tAverage Score:\t10.5783\ttime: 0:00:33.588617\n",
      "Total score (averaged over agents) this episode\t613:\t11.1940\tAverage Score:\t10.5750\ttime: 0:00:33.633085\n",
      "Total score (averaged over agents) this episode\t614:\t10.4125\tAverage Score:\t10.5608\ttime: 0:00:33.615570\n",
      "Total score (averaged over agents) this episode\t615:\t10.3675\tAverage Score:\t10.5544\ttime: 0:00:33.585574\n",
      "Total score (averaged over agents) this episode\t616:\t14.1750\tAverage Score:\t10.5692\ttime: 0:00:33.575575\n",
      "Total score (averaged over agents) this episode\t617:\t12.4245\tAverage Score:\t10.5751\ttime: 0:00:33.604125\n",
      "Total score (averaged over agents) this episode\t618:\t12.4800\tAverage Score:\t10.6011\ttime: 0:00:33.648589\n",
      "Total score (averaged over agents) this episode\t619:\t11.7670\tAverage Score:\t10.6145\ttime: 0:00:33.577110\n",
      "Total score (averaged over agents) this episode\t620:\t11.3545\tAverage Score:\t10.6199\ttime: 0:00:33.646091\n",
      "Total score (averaged over agents) this episode\t621:\t13.2365\tAverage Score:\t10.6427\ttime: 0:00:33.570572\n",
      "Total score (averaged over agents) this episode\t622:\t14.7245\tAverage Score:\t10.6886\ttime: 0:00:33.610589\n",
      "Total score (averaged over agents) this episode\t623:\t14.1225\tAverage Score:\t10.7018\ttime: 0:00:33.539559\n",
      "Total score (averaged over agents) this episode\t624:\t15.5490\tAverage Score:\t10.7487\ttime: 0:00:33.463545\n",
      "Total score (averaged over agents) this episode\t625:\t13.2340\tAverage Score:\t10.7597\ttime: 0:00:33.375065\n",
      "Total score (averaged over agents) this episode\t626:\t11.4145\tAverage Score:\t10.7518\ttime: 0:00:33.569479\n",
      "Total score (averaged over agents) this episode\t627:\t14.6095\tAverage Score:\t10.7780\ttime: 0:00:33.351540\n",
      "Total score (averaged over agents) this episode\t628:\t13.7105\tAverage Score:\t10.7983\ttime: 0:00:33.421536\n",
      "Total score (averaged over agents) this episode\t629:\t14.0400\tAverage Score:\t10.8174\ttime: 0:00:33.497557\n",
      "Total score (averaged over agents) this episode\t630:\t15.4835\tAverage Score:\t10.8421\ttime: 0:00:33.478542\n",
      "Total score (averaged over agents) this episode\t631:\t13.4025\tAverage Score:\t10.8528\ttime: 0:00:33.538560\n",
      "Total score (averaged over agents) this episode\t632:\t11.2835\tAverage Score:\t10.8448\ttime: 0:00:33.545558\n",
      "Total score (averaged over agents) this episode\t633:\t9.9550\tAverage Score:\t10.8275\ttime: 0:00:33.603114\n",
      "Total score (averaged over agents) this episode\t634:\t10.9585\tAverage Score:\t10.8273\ttime: 0:00:33.552065\n",
      "Total score (averaged over agents) this episode\t635:\t11.2360\tAverage Score:\t10.8119\ttime: 0:00:33.646589\n",
      "Total score (averaged over agents) this episode\t636:\t10.1965\tAverage Score:\t10.7822\ttime: 0:00:33.613071\n",
      "Total score (averaged over agents) this episode\t637:\t9.1815\tAverage Score:\t10.7538\ttime: 0:00:33.628585\n",
      "Total score (averaged over agents) this episode\t638:\t11.3315\tAverage Score:\t10.7514\ttime: 0:00:33.721615\n",
      "Total score (averaged over agents) this episode\t639:\t14.9555\tAverage Score:\t10.7918\ttime: 0:00:33.582083\n",
      "Total score (averaged over agents) this episode\t640:\t17.1820\tAverage Score:\t10.8557\ttime: 0:00:33.550103\n",
      "Total score (averaged over agents) this episode\t641:\t15.1050\tAverage Score:\t10.8948\ttime: 0:00:33.559062\n",
      "Total score (averaged over agents) this episode\t642:\t16.4940\tAverage Score:\t10.9410\ttime: 0:00:33.619585\n",
      "Total score (averaged over agents) this episode\t643:\t21.8180\tAverage Score:\t11.0487\ttime: 0:00:33.550585\n",
      "Total score (averaged over agents) this episode\t644:\t20.3960\tAverage Score:\t11.1331\ttime: 0:00:33.478551\n",
      "Total score (averaged over agents) this episode\t645:\t19.4760\tAverage Score:\t11.2270\ttime: 0:00:33.531562\n",
      "Total score (averaged over agents) this episode\t646:\t20.8765\tAverage Score:\t11.3331\ttime: 0:00:33.404070\n",
      "Total score (averaged over agents) this episode\t647:\t17.4995\tAverage Score:\t11.3960\ttime: 0:00:33.482056\n",
      "Total score (averaged over agents) this episode\t648:\t16.4440\tAverage Score:\t11.4391\ttime: 0:00:33.404520\n",
      "Total score (averaged over agents) this episode\t649:\t15.6065\tAverage Score:\t11.4899\ttime: 0:00:33.486548\n",
      "Total score (averaged over agents) this episode\t650:\t14.7115\tAverage Score:\t11.5210\ttime: 0:00:33.442554\n",
      "Total score (averaged over agents) this episode\t651:\t15.2730\tAverage Score:\t11.5683\ttime: 0:00:33.499546\n",
      "Total score (averaged over agents) this episode\t652:\t16.2270\tAverage Score:\t11.6123\ttime: 0:00:33.552105\n",
      "Total score (averaged over agents) this episode\t653:\t15.8275\tAverage Score:\t11.6631\ttime: 0:00:33.822111\n",
      "Total score (averaged over agents) this episode\t654:\t16.8495\tAverage Score:\t11.7477\ttime: 0:00:34.450771\n",
      "Total score (averaged over agents) this episode\t655:\t16.7275\tAverage Score:\t11.9079\ttime: 0:00:34.674811\n",
      "Total score (averaged over agents) this episode\t656:\t18.8205\tAverage Score:\t12.0928\ttime: 0:00:34.333732\n",
      "Total score (averaged over agents) this episode\t657:\t23.6760\tAverage Score:\t12.2894\ttime: 0:00:34.219717\n",
      "Total score (averaged over agents) this episode\t658:\t20.4805\tAverage Score:\t12.4381\ttime: 0:00:33.563590\n",
      "Total score (averaged over agents) this episode\t659:\t23.2960\tAverage Score:\t12.6048\ttime: 0:00:33.615119\n",
      "Total score (averaged over agents) this episode\t660:\t25.8325\tAverage Score:\t12.7804\ttime: 0:00:33.583049\n",
      "Total score (averaged over agents) this episode\t661:\t24.4045\tAverage Score:\t12.9357\ttime: 0:00:33.649580\n",
      "Total score (averaged over agents) this episode\t662:\t21.3335\tAverage Score:\t13.0892\ttime: 0:00:33.643091\n",
      "Total score (averaged over agents) this episode\t663:\t21.9865\tAverage Score:\t13.2330\ttime: 0:00:33.536055\n",
      "Total score (averaged over agents) this episode\t664:\t23.6580\tAverage Score:\t13.3717\ttime: 0:00:33.429524\n",
      "Total score (averaged over agents) this episode\t665:\t23.2295\tAverage Score:\t13.5141\ttime: 0:00:33.493044\n",
      "Total score (averaged over agents) this episode\t666:\t25.3155\tAverage Score:\t13.6780\ttime: 0:00:33.399576\n",
      "Total score (averaged over agents) this episode\t667:\t27.2615\tAverage Score:\t13.8473\ttime: 0:00:33.444036\n",
      "Total score (averaged over agents) this episode\t668:\t25.6950\tAverage Score:\t14.0099\ttime: 0:00:33.415529\n",
      "Total score (averaged over agents) this episode\t669:\t28.1830\tAverage Score:\t14.1847\ttime: 0:00:33.470543\n",
      "Total score (averaged over agents) this episode\t670:\t30.5320\tAverage Score:\t14.3963\ttime: 0:00:33.462545\n",
      "Total score (averaged over agents) this episode\t671:\t35.2505\tAverage Score:\t14.6578\ttime: 0:00:33.490539\n",
      "Total score (averaged over agents) this episode\t672:\t35.0180\tAverage Score:\t14.9068\ttime: 0:00:33.610084\n",
      "Total score (averaged over agents) this episode\t673:\t34.4860\tAverage Score:\t15.1566\ttime: 0:00:33.651129\n",
      "Total score (averaged over agents) this episode\t674:\t36.5910\tAverage Score:\t15.4154\ttime: 0:00:33.743109\n",
      "Total score (averaged over agents) this episode\t675:\t36.3745\tAverage Score:\t15.6698\ttime: 0:00:33.586585\n",
      "Total score (averaged over agents) this episode\t676:\t36.3825\tAverage Score:\t15.9358\ttime: 0:00:33.523545\n",
      "Total score (averaged over agents) this episode\t677:\t35.3890\tAverage Score:\t16.2021\ttime: 0:00:33.583571\n",
      "Total score (averaged over agents) this episode\t678:\t32.5920\tAverage Score:\t16.4323\ttime: 0:00:33.537574\n",
      "Total score (averaged over agents) this episode\t679:\t33.4370\tAverage Score:\t16.6759\ttime: 0:00:33.689135\n",
      "Total score (averaged over agents) this episode\t680:\t32.6160\tAverage Score:\t16.9055\ttime: 0:00:33.601069\n",
      "Total score (averaged over agents) this episode\t681:\t34.2925\tAverage Score:\t17.1380\ttime: 0:00:33.500566\n",
      "Total score (averaged over agents) this episode\t682:\t34.7820\tAverage Score:\t17.3768\ttime: 0:00:33.561064\n",
      "Total score (averaged over agents) this episode\t683:\t35.4200\tAverage Score:\t17.6348\ttime: 0:00:33.654104\n",
      "Total score (averaged over agents) this episode\t684:\t35.0550\tAverage Score:\t17.8759\ttime: 0:00:33.436544\n",
      "Total score (averaged over agents) this episode\t685:\t35.2460\tAverage Score:\t18.1207\ttime: 0:00:33.455530\n",
      "Total score (averaged over agents) this episode\t686:\t35.0925\tAverage Score:\t18.3548\ttime: 0:00:33.295047\n",
      "Total score (averaged over agents) this episode\t687:\t34.4205\tAverage Score:\t18.5883\ttime: 0:00:33.296996\n",
      "Total score (averaged over agents) this episode\t688:\t34.5760\tAverage Score:\t18.8179\ttime: 0:00:33.307526\n",
      "Total score (averaged over agents) this episode\t689:\t30.3860\tAverage Score:\t19.0044\ttime: 0:00:33.410545\n",
      "Total score (averaged over agents) this episode\t690:\t34.5965\tAverage Score:\t19.2408\ttime: 0:00:33.442547\n",
      "Total score (averaged over agents) this episode\t691:\t38.0815\tAverage Score:\t19.4946\ttime: 0:00:33.424527\n",
      "Total score (averaged over agents) this episode\t692:\t35.7985\tAverage Score:\t19.7534\ttime: 0:00:33.471088\n",
      "Total score (averaged over agents) this episode\t693:\t35.9080\tAverage Score:\t20.0123\ttime: 0:00:33.530071\n",
      "Total score (averaged over agents) this episode\t694:\t36.6435\tAverage Score:\t20.2638\ttime: 0:00:33.490548\n",
      "Total score (averaged over agents) this episode\t695:\t36.7625\tAverage Score:\t20.5207\ttime: 0:00:33.455548\n",
      "Total score (averaged over agents) this episode\t696:\t37.9740\tAverage Score:\t20.7906\ttime: 0:00:33.491552\n",
      "Total score (averaged over agents) this episode\t697:\t38.3575\tAverage Score:\t21.0770\ttime: 0:00:33.465542\n",
      "Total score (averaged over agents) this episode\t698:\t38.4905\tAverage Score:\t21.3578\ttime: 0:00:33.442080\n",
      "Total score (averaged over agents) this episode\t699:\t39.2065\tAverage Score:\t21.6541\ttime: 0:00:33.467045\n",
      "Total score (averaged over agents) this episode\t700:\t39.0725\tAverage Score:\t21.9466\ttime: 0:00:33.506548\n",
      "Episode 700\tAverage Score: 21.95\n",
      "Total score (averaged over agents) this episode\t701:\t38.6105\tAverage Score:\t22.2247\ttime: 0:00:33.479579\n",
      "Total score (averaged over agents) this episode\t702:\t38.3270\tAverage Score:\t22.4798\ttime: 0:00:33.435538\n",
      "Total score (averaged over agents) this episode\t703:\t38.1625\tAverage Score:\t22.7439\ttime: 0:00:33.400520\n",
      "Total score (averaged over agents) this episode\t704:\t36.8035\tAverage Score:\t22.9619\ttime: 0:00:33.327053\n",
      "Total score (averaged over agents) this episode\t705:\t37.0510\tAverage Score:\t23.1924\ttime: 0:00:33.262003\n",
      "Total score (averaged over agents) this episode\t706:\t37.4980\tAverage Score:\t23.4332\ttime: 0:00:33.272521\n",
      "Total score (averaged over agents) this episode\t707:\t39.0740\tAverage Score:\t23.6943\ttime: 0:00:33.358511\n",
      "Total score (averaged over agents) this episode\t708:\t38.9000\tAverage Score:\t23.9462\ttime: 0:00:33.308511\n",
      "Total score (averaged over agents) this episode\t709:\t37.8805\tAverage Score:\t24.2180\ttime: 0:00:33.491545\n",
      "Total score (averaged over agents) this episode\t710:\t39.1700\tAverage Score:\t24.5077\ttime: 0:00:33.365521\n",
      "Total score (averaged over agents) this episode\t711:\t38.9555\tAverage Score:\t24.7747\ttime: 0:00:33.351059\n",
      "Total score (averaged over agents) this episode\t712:\t38.8760\tAverage Score:\t25.0462\ttime: 0:00:33.458048\n",
      "Total score (averaged over agents) this episode\t713:\t38.5075\tAverage Score:\t25.3194\ttime: 0:00:33.449550\n",
      "Total score (averaged over agents) this episode\t714:\t36.1275\tAverage Score:\t25.5765\ttime: 0:00:33.453532\n",
      "Total score (averaged over agents) this episode\t715:\t35.1775\tAverage Score:\t25.8246\ttime: 0:00:33.419527\n",
      "Total score (averaged over agents) this episode\t716:\t35.7080\tAverage Score:\t26.0400\ttime: 0:00:33.386526\n",
      "Total score (averaged over agents) this episode\t717:\t37.3350\tAverage Score:\t26.2891\ttime: 0:00:33.391573\n",
      "Total score (averaged over agents) this episode\t718:\t32.6910\tAverage Score:\t26.4912\ttime: 0:00:33.400018\n",
      "Total score (averaged over agents) this episode\t719:\t35.2250\tAverage Score:\t26.7258\ttime: 0:00:33.341528\n",
      "Total score (averaged over agents) this episode\t720:\t33.9090\tAverage Score:\t26.9513\ttime: 0:00:33.443866\n",
      "Total score (averaged over agents) this episode\t721:\t30.9760\tAverage Score:\t27.1287\ttime: 0:00:33.488549\n",
      "Total score (averaged over agents) this episode\t722:\t33.9115\tAverage Score:\t27.3206\ttime: 0:00:33.417525\n",
      "Total score (averaged over agents) this episode\t723:\t31.7710\tAverage Score:\t27.4971\ttime: 0:00:33.289046\n",
      "Total score (averaged over agents) this episode\t724:\t36.5650\tAverage Score:\t27.7072\ttime: 0:00:33.277001\n",
      "Total score (averaged over agents) this episode\t725:\t33.7130\tAverage Score:\t27.9120\ttime: 0:00:33.266496\n",
      "Total score (averaged over agents) this episode\t726:\t33.5495\tAverage Score:\t28.1334\ttime: 0:00:33.256486\n",
      "Total score (averaged over agents) this episode\t727:\t35.1670\tAverage Score:\t28.3389\ttime: 0:00:33.254484\n",
      "Total score (averaged over agents) this episode\t728:\t36.3040\tAverage Score:\t28.5649\ttime: 0:00:33.281513\n",
      "Total score (averaged over agents) this episode\t729:\t34.5765\tAverage Score:\t28.7702\ttime: 0:00:33.293045\n",
      "Total score (averaged over agents) this episode\t730:\t34.2305\tAverage Score:\t28.9577\ttime: 0:00:33.313002\n",
      "Total score (averaged over agents) this episode\t731:\t35.3575\tAverage Score:\t29.1772\ttime: 0:00:33.344506\n",
      "Total score (averaged over agents) this episode\t732:\t34.6390\tAverage Score:\t29.4108\ttime: 0:00:33.395533\n",
      "Total score (averaged over agents) this episode\t733:\t33.5440\tAverage Score:\t29.6467\ttime: 0:00:33.451541\n",
      "Total score (averaged over agents) this episode\t734:\t32.6240\tAverage Score:\t29.8633\ttime: 0:00:33.667586\n",
      "Total score (averaged over agents) this episode\t735:\t37.8005\tAverage Score:\t30.1290\ttime: 0:00:33.385062\n",
      "\n",
      "solved in Episode {} 735\n",
      "Total score (averaged over agents) this episode\t736:\t37.2965\tAverage Score:\t30.4000\ttime: 0:00:33.536045\n",
      "\n",
      "solved in Episode {} 736\n",
      "Total score (averaged over agents) this episode\t737:\t36.0695\tAverage Score:\t30.6689\ttime: 0:00:33.492558\n",
      "\n",
      "solved in Episode {} 737\n",
      "Total score (averaged over agents) this episode\t738:\t37.0595\tAverage Score:\t30.9262\ttime: 0:00:33.496545\n",
      "\n",
      "solved in Episode {} 738\n",
      "Total score (averaged over agents) this episode\t739:\t37.8990\tAverage Score:\t31.1556\ttime: 0:00:33.504576\n",
      "\n",
      "solved in Episode {} 739\n",
      "Total score (averaged over agents) this episode\t740:\t37.4810\tAverage Score:\t31.3586\ttime: 0:00:33.502559\n",
      "\n",
      "solved in Episode {} 740\n",
      "Total score (averaged over agents) this episode\t741:\t37.8415\tAverage Score:\t31.5859\ttime: 0:00:33.485540\n",
      "\n",
      "solved in Episode {} 741\n",
      "Total score (averaged over agents) this episode\t742:\t38.4945\tAverage Score:\t31.8059\ttime: 0:00:33.515600\n",
      "\n",
      "solved in Episode {} 742\n",
      "Total score (averaged over agents) this episode\t743:\t37.4470\tAverage Score:\t31.9622\ttime: 0:00:33.435032\n",
      "\n",
      "solved in Episode {} 743\n",
      "Total score (averaged over agents) this episode\t744:\t37.1965\tAverage Score:\t32.1302\ttime: 0:00:33.371519\n",
      "\n",
      "solved in Episode {} 744\n",
      "Total score (averaged over agents) this episode\t745:\t36.2980\tAverage Score:\t32.2985\ttime: 0:00:33.348513\n",
      "\n",
      "solved in Episode {} 745\n",
      "Total score (averaged over agents) this episode\t746:\t36.2490\tAverage Score:\t32.4522\ttime: 0:00:33.269501\n",
      "\n",
      "solved in Episode {} 746\n",
      "Total score (averaged over agents) this episode\t747:\t37.6975\tAverage Score:\t32.6542\ttime: 0:00:33.233491\n",
      "\n",
      "solved in Episode {} 747\n",
      "Total score (averaged over agents) this episode\t748:\t37.3915\tAverage Score:\t32.8636\ttime: 0:00:33.307050\n",
      "\n",
      "solved in Episode {} 748\n",
      "Total score (averaged over agents) this episode\t749:\t36.6785\tAverage Score:\t33.0744\ttime: 0:00:33.301995\n",
      "\n",
      "solved in Episode {} 749\n",
      "Total score (averaged over agents) this episode\t750:\t38.0295\tAverage Score:\t33.3075\ttime: 0:00:33.397532\n",
      "\n",
      "solved in Episode {} 750\n",
      "Total score (averaged over agents) this episode\t751:\t36.2325\tAverage Score:\t33.5171\ttime: 0:00:33.369513\n",
      "\n",
      "solved in Episode {} 751\n",
      "Total score (averaged over agents) this episode\t752:\t36.0190\tAverage Score:\t33.7151\ttime: 0:00:36.256680\n",
      "\n",
      "solved in Episode {} 752\n",
      "Total score (averaged over agents) this episode\t753:\t37.0625\tAverage Score:\t33.9274\ttime: 0:00:34.111229\n",
      "\n",
      "solved in Episode {} 753\n",
      "Total score (averaged over agents) this episode\t754:\t37.4930\tAverage Score:\t34.1338\ttime: 0:00:33.766153\n",
      "\n",
      "solved in Episode {} 754\n",
      "Total score (averaged over agents) this episode\t755:\t38.2980\tAverage Score:\t34.3495\ttime: 0:00:33.535057\n",
      "\n",
      "solved in Episode {} 755\n",
      "Total score (averaged over agents) this episode\t756:\t37.7975\tAverage Score:\t34.5393\ttime: 0:00:33.668585\n",
      "\n",
      "solved in Episode {} 756\n",
      "Total score (averaged over agents) this episode\t757:\t37.7300\tAverage Score:\t34.6799\ttime: 0:00:34.304262\n",
      "\n",
      "solved in Episode {} 757\n",
      "Total score (averaged over agents) this episode\t758:\t37.2425\tAverage Score:\t34.8475\ttime: 0:00:33.721614\n",
      "\n",
      "solved in Episode {} 758\n",
      "Total score (averaged over agents) this episode\t759:\t36.7005\tAverage Score:\t34.9815\ttime: 0:00:33.571565\n",
      "\n",
      "solved in Episode {} 759\n",
      "Total score (averaged over agents) this episode\t760:\t38.7630\tAverage Score:\t35.1108\ttime: 0:00:33.700156\n",
      "\n",
      "solved in Episode {} 760\n",
      "Total score (averaged over agents) this episode\t761:\t38.1765\tAverage Score:\t35.2485\ttime: 0:00:33.622076\n",
      "\n",
      "solved in Episode {} 761\n",
      "Total score (averaged over agents) this episode\t762:\t37.9235\tAverage Score:\t35.4144\ttime: 0:00:33.599568\n",
      "\n",
      "solved in Episode {} 762\n",
      "Total score (averaged over agents) this episode\t763:\t38.7495\tAverage Score:\t35.5821\ttime: 0:00:33.677606\n",
      "\n",
      "solved in Episode {} 763\n",
      "Total score (averaged over agents) this episode\t764:\t38.9725\tAverage Score:\t35.7352\ttime: 0:00:34.105202\n",
      "\n",
      "solved in Episode {} 764\n",
      "Total score (averaged over agents) this episode\t765:\t37.2085\tAverage Score:\t35.8750\ttime: 0:00:34.933983\n",
      "\n",
      "solved in Episode {} 765\n",
      "Total score (averaged over agents) this episode\t766:\t38.6350\tAverage Score:\t36.0082\ttime: 0:00:33.507550\n",
      "\n",
      "solved in Episode {} 766\n",
      "Total score (averaged over agents) this episode\t767:\t38.2140\tAverage Score:\t36.1177\ttime: 0:00:33.366529\n",
      "\n",
      "solved in Episode {} 767\n",
      "Total score (averaged over agents) this episode\t768:\t38.3290\tAverage Score:\t36.2441\ttime: 0:00:33.827662\n",
      "\n",
      "solved in Episode {} 768\n",
      "Total score (averaged over agents) this episode\t769:\t37.2340\tAverage Score:\t36.3346\ttime: 0:00:37.100459\n",
      "\n",
      "solved in Episode {} 769\n",
      "Total score (averaged over agents) this episode\t770:\t36.4175\tAverage Score:\t36.3934\ttime: 0:00:35.872241\n",
      "\n",
      "solved in Episode {} 770\n",
      "Total score (averaged over agents) this episode\t771:\t38.1325\tAverage Score:\t36.4223\ttime: 0:00:35.527085\n",
      "\n",
      "solved in Episode {} 771\n",
      "Total score (averaged over agents) this episode\t772:\t38.1410\tAverage Score:\t36.4535\ttime: 0:00:36.441759\n",
      "\n",
      "solved in Episode {} 772\n",
      "Total score (averaged over agents) this episode\t773:\t38.0080\tAverage Score:\t36.4887\ttime: 0:00:36.998422\n",
      "\n",
      "solved in Episode {} 773\n",
      "Total score (averaged over agents) this episode\t774:\t36.7940\tAverage Score:\t36.4907\ttime: 0:00:36.957346\n",
      "\n",
      "solved in Episode {} 774\n",
      "Total score (averaged over agents) this episode\t775:\t37.7485\tAverage Score:\t36.5045\ttime: 0:00:36.793895\n",
      "\n",
      "solved in Episode {} 775\n",
      "Total score (averaged over agents) this episode\t776:\t38.0145\tAverage Score:\t36.5208\ttime: 0:00:36.804944\n",
      "\n",
      "solved in Episode {} 776\n",
      "Total score (averaged over agents) this episode\t777:\t37.1945\tAverage Score:\t36.5389\ttime: 0:00:36.201790\n",
      "\n",
      "solved in Episode {} 777\n",
      "Total score (averaged over agents) this episode\t778:\t36.5775\tAverage Score:\t36.5787\ttime: 0:00:36.481284\n",
      "\n",
      "solved in Episode {} 778\n",
      "Total score (averaged over agents) this episode\t779:\t36.0695\tAverage Score:\t36.6050\ttime: 0:00:36.461982\n",
      "\n",
      "solved in Episode {} 779\n",
      "Total score (averaged over agents) this episode\t780:\t36.6020\tAverage Score:\t36.6449\ttime: 0:00:36.411689\n",
      "\n",
      "solved in Episode {} 780\n",
      "Total score (averaged over agents) this episode\t781:\t34.9325\tAverage Score:\t36.6513\ttime: 0:00:36.742879\n",
      "\n",
      "solved in Episode {} 781\n",
      "Total score (averaged over agents) this episode\t782:\t36.3125\tAverage Score:\t36.6666\ttime: 0:00:36.040220\n",
      "\n",
      "solved in Episode {} 782\n",
      "Total score (averaged over agents) this episode\t783:\t28.8470\tAverage Score:\t36.6009\ttime: 0:00:36.268756\n",
      "\n",
      "solved in Episode {} 783\n",
      "Total score (averaged over agents) this episode\t784:\t30.6085\tAverage Score:\t36.5564\ttime: 0:00:36.619824\n",
      "\n",
      "solved in Episode {} 784\n",
      "Total score (averaged over agents) this episode\t785:\t30.8865\tAverage Score:\t36.5128\ttime: 0:00:34.916877\n",
      "\n",
      "solved in Episode {} 785\n",
      "Total score (averaged over agents) this episode\t786:\t35.0265\tAverage Score:\t36.5121\ttime: 0:00:35.157016\n",
      "\n",
      "solved in Episode {} 786\n",
      "Total score (averaged over agents) this episode\t787:\t34.0890\tAverage Score:\t36.5088\ttime: 0:00:34.229710\n",
      "\n",
      "solved in Episode {} 787\n",
      "Total score (averaged over agents) this episode\t788:\t37.6315\tAverage Score:\t36.5394\ttime: 0:00:34.380748\n",
      "\n",
      "solved in Episode {} 788\n",
      "Total score (averaged over agents) this episode\t789:\t37.7315\tAverage Score:\t36.6128\ttime: 0:00:34.753930\n",
      "\n",
      "solved in Episode {} 789\n",
      "Total score (averaged over agents) this episode\t790:\t35.5510\tAverage Score:\t36.6224\ttime: 0:00:34.567308\n",
      "\n",
      "solved in Episode {} 790\n",
      "Total score (averaged over agents) this episode\t791:\t36.3795\tAverage Score:\t36.6054\ttime: 0:00:34.465273\n",
      "\n",
      "solved in Episode {} 791\n",
      "Total score (averaged over agents) this episode\t792:\t32.1275\tAverage Score:\t36.5687\ttime: 0:00:34.814881\n",
      "\n",
      "solved in Episode {} 792\n",
      "Total score (averaged over agents) this episode\t793:\t31.1495\tAverage Score:\t36.5211\ttime: 0:00:36.332684\n",
      "\n",
      "solved in Episode {} 793\n",
      "Total score (averaged over agents) this episode\t794:\t31.2275\tAverage Score:\t36.4669\ttime: 0:00:37.931518\n",
      "\n",
      "solved in Episode {} 794\n",
      "Total score (averaged over agents) this episode\t795:\t36.4155\tAverage Score:\t36.4634\ttime: 0:00:37.425070\n",
      "\n",
      "solved in Episode {} 795\n",
      "Total score (averaged over agents) this episode\t796:\t36.6360\tAverage Score:\t36.4501\ttime: 0:00:37.729612\n",
      "\n",
      "solved in Episode {} 796\n",
      "Total score (averaged over agents) this episode\t797:\t35.6345\tAverage Score:\t36.4228\ttime: 0:00:36.424254\n",
      "\n",
      "solved in Episode {} 797\n",
      "Total score (averaged over agents) this episode\t798:\t37.6765\tAverage Score:\t36.4147\ttime: 0:00:36.922610\n",
      "\n",
      "solved in Episode {} 798\n",
      "Total score (averaged over agents) this episode\t799:\t38.1275\tAverage Score:\t36.4039\ttime: 0:00:38.087256\n",
      "\n",
      "solved in Episode {} 799\n",
      "Total score (averaged over agents) this episode\t800:\t36.6745\tAverage Score:\t36.3799\ttime: 0:00:45.890902\n",
      "Episode 800\tAverage Score: 36.38\n",
      "\n",
      "solved in Episode {} 800\n",
      "Total score (averaged over agents) this episode\t801:\t33.8280\tAverage Score:\t36.3321\ttime: 0:00:58.520393\n",
      "\n",
      "solved in Episode {} 801\n",
      "Total score (averaged over agents) this episode\t802:\t36.3365\tAverage Score:\t36.3122\ttime: 0:00:47.062864\n",
      "\n",
      "solved in Episode {} 802\n",
      "Total score (averaged over agents) this episode\t803:\t29.2400\tAverage Score:\t36.2230\ttime: 0:00:46.525746\n",
      "\n",
      "solved in Episode {} 803\n",
      "Total score (averaged over agents) this episode\t804:\t33.8150\tAverage Score:\t36.1931\ttime: 0:00:57.343626\n",
      "\n",
      "solved in Episode {} 804\n",
      "Total score (averaged over agents) this episode\t805:\t30.9615\tAverage Score:\t36.1322\ttime: 0:01:03.071021\n",
      "\n",
      "solved in Episode {} 805\n",
      "Total score (averaged over agents) this episode\t806:\t33.4015\tAverage Score:\t36.0912\ttime: 0:01:01.286523\n",
      "\n",
      "solved in Episode {} 806\n",
      "Total score (averaged over agents) this episode\t807:\t32.8775\tAverage Score:\t36.0293\ttime: 0:01:01.252967\n",
      "\n",
      "solved in Episode {} 807\n",
      "Total score (averaged over agents) this episode\t808:\t32.9935\tAverage Score:\t35.9702\ttime: 0:01:01.045164\n",
      "\n",
      "solved in Episode {} 808\n",
      "Total score (averaged over agents) this episode\t809:\t32.2830\tAverage Score:\t35.9142\ttime: 0:01:04.276503\n",
      "\n",
      "solved in Episode {} 809\n",
      "Total score (averaged over agents) this episode\t810:\t32.8425\tAverage Score:\t35.8509\ttime: 0:01:11.864301\n",
      "\n",
      "solved in Episode {} 810\n",
      "Total score (averaged over agents) this episode\t811:\t32.6170\tAverage Score:\t35.7876\ttime: 0:01:09.546960\n",
      "\n",
      "solved in Episode {} 811\n",
      "Total score (averaged over agents) this episode\t812:\t33.4640\tAverage Score:\t35.7334\ttime: 0:01:03.535621\n",
      "\n",
      "solved in Episode {} 812\n",
      "Total score (averaged over agents) this episode\t813:\t31.7895\tAverage Score:\t35.6663\ttime: 0:01:02.713175\n",
      "\n",
      "solved in Episode {} 813\n",
      "Total score (averaged over agents) this episode\t814:\t35.8420\tAverage Score:\t35.6634\ttime: 0:01:03.065414\n",
      "\n",
      "solved in Episode {} 814\n",
      "Total score (averaged over agents) this episode\t815:\t33.2475\tAverage Score:\t35.6441\ttime: 0:00:59.532192\n",
      "\n",
      "solved in Episode {} 815\n",
      "Total score (averaged over agents) this episode\t816:\t33.6680\tAverage Score:\t35.6237\ttime: 0:00:57.204367\n",
      "\n",
      "solved in Episode {} 816\n",
      "Total score (averaged over agents) this episode\t817:\t35.5170\tAverage Score:\t35.6055\ttime: 0:01:06.249234\n",
      "\n",
      "solved in Episode {} 817\n",
      "Total score (averaged over agents) this episode\t818:\t37.1040\tAverage Score:\t35.6497\ttime: 0:01:02.603525\n",
      "\n",
      "solved in Episode {} 818\n",
      "Total score (averaged over agents) this episode\t819:\t37.0195\tAverage Score:\t35.6676\ttime: 0:01:09.545986\n",
      "\n",
      "solved in Episode {} 819\n",
      "Total score (averaged over agents) this episode\t820:\t36.3130\tAverage Score:\t35.6916\ttime: 0:01:06.376507\n",
      "\n",
      "solved in Episode {} 820\n",
      "Total score (averaged over agents) this episode\t821:\t37.7135\tAverage Score:\t35.7590\ttime: 0:01:05.703839\n",
      "\n",
      "solved in Episode {} 821\n",
      "Total score (averaged over agents) this episode\t822:\t37.7230\tAverage Score:\t35.7971\ttime: 0:01:08.426718\n",
      "\n",
      "solved in Episode {} 822\n",
      "Total score (averaged over agents) this episode\t823:\t37.9520\tAverage Score:\t35.8589\ttime: 0:01:07.246190\n",
      "\n",
      "solved in Episode {} 823\n",
      "Total score (averaged over agents) this episode\t824:\t37.8115\tAverage Score:\t35.8714\ttime: 0:01:02.640475\n",
      "\n",
      "solved in Episode {} 824\n",
      "Total score (averaged over agents) this episode\t825:\t37.6495\tAverage Score:\t35.9108\ttime: 0:00:58.591464\n",
      "\n",
      "solved in Episode {} 825\n",
      "Total score (averaged over agents) this episode\t826:\t37.8715\tAverage Score:\t35.9540\ttime: 0:01:00.984293\n",
      "\n",
      "solved in Episode {} 826\n",
      "Total score (averaged over agents) this episode\t827:\t38.2885\tAverage Score:\t35.9852\ttime: 0:01:06.281771\n",
      "\n",
      "solved in Episode {} 827\n",
      "Total score (averaged over agents) this episode\t828:\t35.6530\tAverage Score:\t35.9787\ttime: 0:01:01.765494\n",
      "\n",
      "solved in Episode {} 828\n",
      "Total score (averaged over agents) this episode\t829:\t32.6110\tAverage Score:\t35.9590\ttime: 0:01:02.362905\n",
      "\n",
      "solved in Episode {} 829\n",
      "Total score (averaged over agents) this episode\t830:\t30.8200\tAverage Score:\t35.9249\ttime: 0:01:05.487281\n",
      "\n",
      "solved in Episode {} 830\n",
      "Total score (averaged over agents) this episode\t831:\t27.6230\tAverage Score:\t35.8476\ttime: 0:01:00.668698\n",
      "\n",
      "solved in Episode {} 831\n",
      "Total score (averaged over agents) this episode\t832:\t30.7215\tAverage Score:\t35.8084\ttime: 0:01:01.594072\n",
      "\n",
      "solved in Episode {} 832\n",
      "Total score (averaged over agents) this episode\t833:\t29.0760\tAverage Score:\t35.7637\ttime: 0:01:05.788269\n",
      "\n",
      "solved in Episode {} 833\n",
      "Total score (averaged over agents) this episode\t834:\t26.7545\tAverage Score:\t35.7050\ttime: 0:01:10.418652\n",
      "\n",
      "solved in Episode {} 834\n",
      "Total score (averaged over agents) this episode\t835:\t29.9435\tAverage Score:\t35.6265\ttime: 0:01:11.791201\n",
      "\n",
      "solved in Episode {} 835\n",
      "Total score (averaged over agents) this episode\t836:\t30.3725\tAverage Score:\t35.5572\ttime: 0:01:12.186889\n",
      "\n",
      "solved in Episode {} 836\n",
      "Total score (averaged over agents) this episode\t837:\t28.4630\tAverage Score:\t35.4812\ttime: 0:01:02.406338\n",
      "\n",
      "solved in Episode {} 837\n",
      "Total score (averaged over agents) this episode\t838:\t29.7610\tAverage Score:\t35.4082\ttime: 0:01:08.041579\n",
      "\n",
      "solved in Episode {} 838\n",
      "Total score (averaged over agents) this episode\t839:\t31.1035\tAverage Score:\t35.3402\ttime: 0:01:03.760694\n",
      "\n",
      "solved in Episode {} 839\n",
      "Total score (averaged over agents) this episode\t840:\t36.3030\tAverage Score:\t35.3284\ttime: 0:00:58.151391\n",
      "\n",
      "solved in Episode {} 840\n",
      "Total score (averaged over agents) this episode\t841:\t35.2665\tAverage Score:\t35.3027\ttime: 0:00:59.595851\n",
      "\n",
      "solved in Episode {} 841\n",
      "Total score (averaged over agents) this episode\t842:\t36.0380\tAverage Score:\t35.2781\ttime: 0:01:01.787764\n",
      "\n",
      "solved in Episode {} 842\n",
      "Total score (averaged over agents) this episode\t843:\t34.4590\tAverage Score:\t35.2482\ttime: 0:01:03.448752\n",
      "\n",
      "solved in Episode {} 843\n",
      "Total score (averaged over agents) this episode\t844:\t32.0035\tAverage Score:\t35.1963\ttime: 0:01:03.167233\n",
      "\n",
      "solved in Episode {} 844\n",
      "Total score (averaged over agents) this episode\t845:\t32.2580\tAverage Score:\t35.1559\ttime: 0:01:02.441624\n",
      "\n",
      "solved in Episode {} 845\n",
      "Total score (averaged over agents) this episode\t846:\t32.4455\tAverage Score:\t35.1179\ttime: 0:01:12.307972\n",
      "\n",
      "solved in Episode {} 846\n",
      "Total score (averaged over agents) this episode\t847:\t31.4470\tAverage Score:\t35.0554\ttime: 0:01:21.712133\n",
      "\n",
      "solved in Episode {} 847\n",
      "Total score (averaged over agents) this episode\t848:\t31.3770\tAverage Score:\t34.9952\ttime: 0:01:10.626616\n",
      "\n",
      "solved in Episode {} 848\n",
      "Total score (averaged over agents) this episode\t849:\t31.4545\tAverage Score:\t34.9430\ttime: 0:01:10.935021\n",
      "\n",
      "solved in Episode {} 849\n",
      "Total score (averaged over agents) this episode\t850:\t28.0770\tAverage Score:\t34.8435\ttime: 0:01:05.901082\n",
      "\n",
      "solved in Episode {} 850\n",
      "Total score (averaged over agents) this episode\t851:\t30.6390\tAverage Score:\t34.7875\ttime: 0:01:08.932071\n",
      "\n",
      "solved in Episode {} 851\n",
      "Total score (averaged over agents) this episode\t852:\t33.3690\tAverage Score:\t34.7610\ttime: 0:01:02.223775\n",
      "\n",
      "solved in Episode {} 852\n",
      "Total score (averaged over agents) this episode\t853:\t34.9560\tAverage Score:\t34.7400\ttime: 0:00:56.968290\n",
      "\n",
      "solved in Episode {} 853\n",
      "Total score (averaged over agents) this episode\t854:\t33.0830\tAverage Score:\t34.6959\ttime: 0:00:57.758582\n",
      "\n",
      "solved in Episode {} 854\n",
      "Total score (averaged over agents) this episode\t855:\t36.1450\tAverage Score:\t34.6743\ttime: 0:01:00.373086\n",
      "\n",
      "solved in Episode {} 855\n",
      "Total score (averaged over agents) this episode\t856:\t35.6735\tAverage Score:\t34.6531\ttime: 0:01:09.685955\n",
      "\n",
      "solved in Episode {} 856\n",
      "Total score (averaged over agents) this episode\t857:\t37.1025\tAverage Score:\t34.6468\ttime: 0:01:04.499488\n",
      "\n",
      "solved in Episode {} 857\n",
      "Total score (averaged over agents) this episode\t858:\t35.4025\tAverage Score:\t34.6284\ttime: 0:01:02.386743\n",
      "\n",
      "solved in Episode {} 858\n",
      "Total score (averaged over agents) this episode\t859:\t35.5175\tAverage Score:\t34.6166\ttime: 0:00:58.804366\n",
      "\n",
      "solved in Episode {} 859\n",
      "Total score (averaged over agents) this episode\t860:\t34.4535\tAverage Score:\t34.5735\ttime: 0:01:00.397705\n",
      "\n",
      "solved in Episode {} 860\n",
      "Total score (averaged over agents) this episode\t861:\t32.5745\tAverage Score:\t34.5175\ttime: 0:00:58.918209\n",
      "\n",
      "solved in Episode {} 861\n",
      "Total score (averaged over agents) this episode\t862:\t33.0655\tAverage Score:\t34.4689\ttime: 0:00:57.807406\n",
      "\n",
      "solved in Episode {} 862\n",
      "Total score (averaged over agents) this episode\t863:\t31.5390\tAverage Score:\t34.3968\ttime: 0:00:59.238944\n",
      "\n",
      "solved in Episode {} 863\n",
      "Total score (averaged over agents) this episode\t864:\t32.9475\tAverage Score:\t34.3365\ttime: 0:01:02.539565\n",
      "\n",
      "solved in Episode {} 864\n",
      "Total score (averaged over agents) this episode\t865:\t34.1565\tAverage Score:\t34.3060\ttime: 0:01:05.579689\n",
      "\n",
      "solved in Episode {} 865\n",
      "Total score (averaged over agents) this episode\t866:\t32.7070\tAverage Score:\t34.2467\ttime: 0:01:03.380201\n",
      "\n",
      "solved in Episode {} 866\n",
      "Total score (averaged over agents) this episode\t867:\t34.6225\tAverage Score:\t34.2108\ttime: 0:01:01.771511\n",
      "\n",
      "solved in Episode {} 867\n",
      "Total score (averaged over agents) this episode\t868:\t35.8275\tAverage Score:\t34.1858\ttime: 0:00:58.398365\n",
      "\n",
      "solved in Episode {} 868\n",
      "Total score (averaged over agents) this episode\t869:\t34.9575\tAverage Score:\t34.1630\ttime: 0:00:59.338353\n",
      "\n",
      "solved in Episode {} 869\n",
      "Total score (averaged over agents) this episode\t870:\t35.9315\tAverage Score:\t34.1582\ttime: 0:01:01.573801\n",
      "\n",
      "solved in Episode {} 870\n",
      "Total score (averaged over agents) this episode\t871:\t35.9980\tAverage Score:\t34.1368\ttime: 0:01:00.995917\n",
      "\n",
      "solved in Episode {} 871\n",
      "Total score (averaged over agents) this episode\t872:\t34.9975\tAverage Score:\t34.1054\ttime: 0:00:57.177907\n",
      "\n",
      "solved in Episode {} 872\n",
      "Total score (averaged over agents) this episode\t873:\t34.7820\tAverage Score:\t34.0731\ttime: 0:00:59.598352\n",
      "\n",
      "solved in Episode {} 873\n",
      "Total score (averaged over agents) this episode\t874:\t35.9045\tAverage Score:\t34.0643\ttime: 0:00:58.444148\n",
      "\n",
      "solved in Episode {} 874\n",
      "Total score (averaged over agents) this episode\t875:\t32.1850\tAverage Score:\t34.0086\ttime: 0:00:55.920926\n",
      "\n",
      "solved in Episode {} 875\n",
      "Total score (averaged over agents) this episode\t876:\t35.9335\tAverage Score:\t33.9878\ttime: 0:01:02.034351\n",
      "\n",
      "solved in Episode {} 876\n",
      "Total score (averaged over agents) this episode\t877:\t33.2465\tAverage Score:\t33.9483\ttime: 0:01:05.702072\n",
      "\n",
      "solved in Episode {} 877\n",
      "Total score (averaged over agents) this episode\t878:\t37.6575\tAverage Score:\t33.9591\ttime: 0:01:00.389892\n",
      "\n",
      "solved in Episode {} 878\n",
      "Total score (averaged over agents) this episode\t879:\t37.3510\tAverage Score:\t33.9719\ttime: 0:00:59.252818\n",
      "\n",
      "solved in Episode {} 879\n",
      "Total score (averaged over agents) this episode\t880:\t37.4405\tAverage Score:\t33.9803\ttime: 0:00:59.127017\n",
      "\n",
      "solved in Episode {} 880\n",
      "Total score (averaged over agents) this episode\t881:\t37.3210\tAverage Score:\t34.0042\ttime: 0:00:56.945115\n",
      "\n",
      "solved in Episode {} 881\n",
      "Total score (averaged over agents) this episode\t882:\t36.0430\tAverage Score:\t34.0015\ttime: 0:00:59.558136\n",
      "\n",
      "solved in Episode {} 882\n",
      "Total score (averaged over agents) this episode\t883:\t37.3785\tAverage Score:\t34.0868\ttime: 0:00:56.943231\n",
      "\n",
      "solved in Episode {} 883\n",
      "Total score (averaged over agents) this episode\t884:\t33.0895\tAverage Score:\t34.1116\ttime: 0:00:54.285842\n",
      "\n",
      "solved in Episode {} 884\n",
      "Total score (averaged over agents) this episode\t885:\t34.5590\tAverage Score:\t34.1484\ttime: 0:00:54.627474\n",
      "\n",
      "solved in Episode {} 885\n",
      "Total score (averaged over agents) this episode\t886:\t33.1640\tAverage Score:\t34.1297\ttime: 0:00:53.705797\n",
      "\n",
      "solved in Episode {} 886\n",
      "Total score (averaged over agents) this episode\t887:\t34.9555\tAverage Score:\t34.1384\ttime: 0:00:54.188097\n",
      "\n",
      "solved in Episode {} 887\n",
      "Total score (averaged over agents) this episode\t888:\t36.1975\tAverage Score:\t34.1241\ttime: 0:00:56.531803\n",
      "\n",
      "solved in Episode {} 888\n",
      "Total score (averaged over agents) this episode\t889:\t35.3680\tAverage Score:\t34.1004\ttime: 0:00:56.761218\n",
      "\n",
      "solved in Episode {} 889\n",
      "Total score (averaged over agents) this episode\t890:\t33.3590\tAverage Score:\t34.0785\ttime: 0:00:56.793132\n",
      "\n",
      "solved in Episode {} 890\n",
      "Total score (averaged over agents) this episode\t891:\t34.8025\tAverage Score:\t34.0627\ttime: 0:00:56.812813\n",
      "\n",
      "solved in Episode {} 891\n",
      "Total score (averaged over agents) this episode\t892:\t36.5655\tAverage Score:\t34.1071\ttime: 0:00:57.094547\n",
      "\n",
      "solved in Episode {} 892\n",
      "Total score (averaged over agents) this episode\t893:\t35.4685\tAverage Score:\t34.1503\ttime: 0:01:05.321878\n",
      "\n",
      "solved in Episode {} 893\n",
      "Total score (averaged over agents) this episode\t894:\t35.1430\tAverage Score:\t34.1895\ttime: 0:01:07.954501\n",
      "\n",
      "solved in Episode {} 894\n",
      "Total score (averaged over agents) this episode\t895:\t36.2635\tAverage Score:\t34.1879\ttime: 0:01:03.180468\n",
      "\n",
      "solved in Episode {} 895\n",
      "Total score (averaged over agents) this episode\t896:\t37.0675\tAverage Score:\t34.1923\ttime: 0:01:03.639279\n",
      "\n",
      "solved in Episode {} 896\n",
      "Total score (averaged over agents) this episode\t897:\t37.9595\tAverage Score:\t34.2155\ttime: 0:00:59.397207\n",
      "\n",
      "solved in Episode {} 897\n",
      "Total score (averaged over agents) this episode\t898:\t36.8215\tAverage Score:\t34.2070\ttime: 0:01:03.532820\n",
      "\n",
      "solved in Episode {} 898\n",
      "Total score (averaged over agents) this episode\t899:\t34.5710\tAverage Score:\t34.1714\ttime: 0:01:03.493038\n",
      "\n",
      "solved in Episode {} 899\n",
      "Total score (averaged over agents) this episode\t900:\t35.9505\tAverage Score:\t34.1642\ttime: 0:01:01.652910\n",
      "Episode 900\tAverage Score: 34.16\n",
      "\n",
      "solved in Episode {} 900\n",
      "Total score (averaged over agents) this episode\t901:\t35.3305\tAverage Score:\t34.1792\ttime: 0:01:13.317525\n",
      "\n",
      "solved in Episode {} 901\n",
      "Total score (averaged over agents) this episode\t902:\t36.6105\tAverage Score:\t34.1819\ttime: 0:01:18.272812\n",
      "\n",
      "solved in Episode {} 902\n",
      "Total score (averaged over agents) this episode\t903:\t35.3620\tAverage Score:\t34.2431\ttime: 0:01:11.152972\n",
      "\n",
      "solved in Episode {} 903\n",
      "Total score (averaged over agents) this episode\t904:\t30.8740\tAverage Score:\t34.2137\ttime: 0:01:12.957195\n",
      "\n",
      "solved in Episode {} 904\n",
      "Total score (averaged over agents) this episode\t905:\t31.1750\tAverage Score:\t34.2159\ttime: 0:01:09.323724\n",
      "\n",
      "solved in Episode {} 905\n",
      "Total score (averaged over agents) this episode\t906:\t35.9490\tAverage Score:\t34.2413\ttime: 0:01:11.056616\n",
      "\n",
      "solved in Episode {} 906\n",
      "Total score (averaged over agents) this episode\t907:\t33.2035\tAverage Score:\t34.2446\ttime: 0:01:13.783927\n",
      "\n",
      "solved in Episode {} 907\n",
      "Total score (averaged over agents) this episode\t908:\t30.1210\tAverage Score:\t34.2159\ttime: 0:01:10.823666\n",
      "\n",
      "solved in Episode {} 908\n",
      "Total score (averaged over agents) this episode\t909:\t31.2935\tAverage Score:\t34.2060\ttime: 0:01:13.697730\n",
      "\n",
      "solved in Episode {} 909\n",
      "Total score (averaged over agents) this episode\t910:\t24.7065\tAverage Score:\t34.1246\ttime: 0:01:13.505923\n",
      "\n",
      "solved in Episode {} 910\n",
      "Total score (averaged over agents) this episode\t911:\t25.4085\tAverage Score:\t34.0525\ttime: 0:01:09.365974\n",
      "\n",
      "solved in Episode {} 911\n",
      "Total score (averaged over agents) this episode\t912:\t27.9385\tAverage Score:\t33.9973\ttime: 0:01:07.628969\n",
      "\n",
      "solved in Episode {} 912\n",
      "Total score (averaged over agents) this episode\t913:\t27.2360\tAverage Score:\t33.9517\ttime: 0:01:01.329403\n",
      "\n",
      "solved in Episode {} 913\n",
      "Total score (averaged over agents) this episode\t914:\t22.9440\tAverage Score:\t33.8228\ttime: 0:01:09.979946\n",
      "\n",
      "solved in Episode {} 914\n",
      "Total score (averaged over agents) this episode\t915:\t23.8995\tAverage Score:\t33.7293\ttime: 0:01:13.388115\n",
      "\n",
      "solved in Episode {} 915\n",
      "Total score (averaged over agents) this episode\t916:\t18.5225\tAverage Score:\t33.5778\ttime: 0:01:05.230351\n",
      "\n",
      "solved in Episode {} 916\n",
      "Total score (averaged over agents) this episode\t917:\t21.5390\tAverage Score:\t33.4381\ttime: 0:01:13.518910\n",
      "\n",
      "solved in Episode {} 917\n",
      "Total score (averaged over agents) this episode\t918:\t24.4495\tAverage Score:\t33.3115\ttime: 0:01:16.367726\n",
      "\n",
      "solved in Episode {} 918\n",
      "Total score (averaged over agents) this episode\t919:\t25.9780\tAverage Score:\t33.2011\ttime: 0:01:17.015453\n",
      "\n",
      "solved in Episode {} 919\n",
      "Total score (averaged over agents) this episode\t920:\t25.5950\tAverage Score:\t33.0939\ttime: 0:01:09.534224\n",
      "\n",
      "solved in Episode {} 920\n",
      "Total score (averaged over agents) this episode\t921:\t22.2715\tAverage Score:\t32.9395\ttime: 0:01:06.349916\n",
      "\n",
      "solved in Episode {} 921\n",
      "Total score (averaged over agents) this episode\t922:\t16.1775\tAverage Score:\t32.7240\ttime: 0:01:04.340998\n",
      "\n",
      "solved in Episode {} 922\n",
      "Total score (averaged over agents) this episode\t923:\t18.3215\tAverage Score:\t32.5277\ttime: 0:01:03.585965\n",
      "\n",
      "solved in Episode {} 923\n",
      "Total score (averaged over agents) this episode\t924:\t19.1855\tAverage Score:\t32.3415\ttime: 0:01:06.380131\n",
      "\n",
      "solved in Episode {} 924\n",
      "Total score (averaged over agents) this episode\t925:\t24.3200\tAverage Score:\t32.2082\ttime: 0:01:17.147358\n",
      "\n",
      "solved in Episode {} 925\n",
      "Total score (averaged over agents) this episode\t926:\t21.5650\tAverage Score:\t32.0451\ttime: 0:01:18.721567\n",
      "\n",
      "solved in Episode {} 926\n",
      "Total score (averaged over agents) this episode\t927:\t21.4735\tAverage Score:\t31.8770\ttime: 0:01:18.459368\n",
      "\n",
      "solved in Episode {} 927\n",
      "Total score (averaged over agents) this episode\t928:\t28.5500\tAverage Score:\t31.8059\ttime: 0:01:18.257362\n",
      "\n",
      "solved in Episode {} 928\n",
      "Total score (averaged over agents) this episode\t929:\t30.8325\tAverage Score:\t31.7881\ttime: 0:01:20.219894\n",
      "\n",
      "solved in Episode {} 929\n",
      "Total score (averaged over agents) this episode\t930:\t30.6630\tAverage Score:\t31.7866\ttime: 0:01:20.228546\n",
      "\n",
      "solved in Episode {} 930\n",
      "Total score (averaged over agents) this episode\t931:\t29.3855\tAverage Score:\t31.8042\ttime: 0:01:22.722845\n",
      "\n",
      "solved in Episode {} 931\n",
      "Total score (averaged over agents) this episode\t932:\t31.5605\tAverage Score:\t31.8126\ttime: 0:01:19.709819\n",
      "\n",
      "solved in Episode {} 932\n",
      "Total score (averaged over agents) this episode\t933:\t31.0275\tAverage Score:\t31.8321\ttime: 0:01:18.816333\n",
      "\n",
      "solved in Episode {} 933\n",
      "Total score (averaged over agents) this episode\t934:\t31.7430\tAverage Score:\t31.8820\ttime: 0:01:13.947747\n",
      "\n",
      "solved in Episode {} 934\n",
      "Total score (averaged over agents) this episode\t935:\t32.0125\tAverage Score:\t31.9027\ttime: 0:01:08.608088\n",
      "\n",
      "solved in Episode {} 935\n",
      "Total score (averaged over agents) this episode\t936:\t30.0220\tAverage Score:\t31.8992\ttime: 0:01:11.679354\n",
      "\n",
      "solved in Episode {} 936\n",
      "Total score (averaged over agents) this episode\t937:\t30.9810\tAverage Score:\t31.9244\ttime: 0:01:04.861139\n",
      "\n",
      "solved in Episode {} 937\n",
      "Total score (averaged over agents) this episode\t938:\t30.8840\tAverage Score:\t31.9356\ttime: 0:01:09.536099\n",
      "\n",
      "solved in Episode {} 938\n",
      "Total score (averaged over agents) this episode\t939:\t30.5200\tAverage Score:\t31.9298\ttime: 0:01:08.600007\n",
      "\n",
      "solved in Episode {} 939\n",
      "Total score (averaged over agents) this episode\t940:\t27.5710\tAverage Score:\t31.8424\ttime: 0:01:04.566843\n",
      "\n",
      "solved in Episode {} 940\n",
      "Total score (averaged over agents) this episode\t941:\t27.0885\tAverage Score:\t31.7607\ttime: 0:01:03.880048\n",
      "\n",
      "solved in Episode {} 941\n",
      "Total score (averaged over agents) this episode\t942:\t29.3645\tAverage Score:\t31.6939\ttime: 0:01:08.279793\n",
      "\n",
      "solved in Episode {} 942\n",
      "Total score (averaged over agents) this episode\t943:\t33.6860\tAverage Score:\t31.6862\ttime: 0:01:09.174332\n",
      "\n",
      "solved in Episode {} 943\n",
      "Total score (averaged over agents) this episode\t944:\t38.6035\tAverage Score:\t31.7522\ttime: 0:01:12.509261\n",
      "\n",
      "solved in Episode {} 944\n",
      "Total score (averaged over agents) this episode\t945:\t33.9420\tAverage Score:\t31.7690\ttime: 0:01:22.818317\n",
      "\n",
      "solved in Episode {} 945\n",
      "Total score (averaged over agents) this episode\t946:\t36.1740\tAverage Score:\t31.8063\ttime: 0:01:21.176772\n",
      "\n",
      "solved in Episode {} 946\n",
      "Total score (averaged over agents) this episode\t947:\t36.3920\tAverage Score:\t31.8558\ttime: 0:01:08.315661\n",
      "\n",
      "solved in Episode {} 947\n",
      "Total score (averaged over agents) this episode\t948:\t35.0665\tAverage Score:\t31.8927\ttime: 0:01:12.537280\n",
      "\n",
      "solved in Episode {} 948\n",
      "Total score (averaged over agents) this episode\t949:\t38.1525\tAverage Score:\t31.9596\ttime: 0:01:15.376190\n",
      "\n",
      "solved in Episode {} 949\n",
      "Total score (averaged over agents) this episode\t950:\t38.0540\tAverage Score:\t32.0594\ttime: 0:01:13.543580\n",
      "\n",
      "solved in Episode {} 950\n",
      "Total score (averaged over agents) this episode\t951:\t36.9765\tAverage Score:\t32.1228\ttime: 0:01:17.416439\n",
      "\n",
      "solved in Episode {} 951\n",
      "Total score (averaged over agents) this episode\t952:\t37.6690\tAverage Score:\t32.1658\ttime: 0:01:16.085783\n",
      "\n",
      "solved in Episode {} 952\n",
      "Total score (averaged over agents) this episode\t953:\t37.0820\tAverage Score:\t32.1870\ttime: 0:01:07.023217\n",
      "\n",
      "solved in Episode {} 953\n",
      "Total score (averaged over agents) this episode\t954:\t36.8565\tAverage Score:\t32.2248\ttime: 0:01:03.037941\n",
      "\n",
      "solved in Episode {} 954\n",
      "Total score (averaged over agents) this episode\t955:\t36.7615\tAverage Score:\t32.2309\ttime: 0:01:04.143258\n",
      "\n",
      "solved in Episode {} 955\n",
      "Total score (averaged over agents) this episode\t956:\t36.4070\tAverage Score:\t32.2383\ttime: 0:01:02.170965\n",
      "\n",
      "solved in Episode {} 956\n",
      "Total score (averaged over agents) this episode\t957:\t36.8295\tAverage Score:\t32.2355\ttime: 0:01:00.844883\n",
      "\n",
      "solved in Episode {} 957\n",
      "Total score (averaged over agents) this episode\t958:\t35.7900\tAverage Score:\t32.2394\ttime: 0:00:57.148278\n",
      "\n",
      "solved in Episode {} 958\n",
      "Total score (averaged over agents) this episode\t959:\t36.7465\tAverage Score:\t32.2517\ttime: 0:01:15.031221\n",
      "\n",
      "solved in Episode {} 959\n",
      "Total score (averaged over agents) this episode\t960:\t36.1370\tAverage Score:\t32.2685\ttime: 0:01:15.862765\n",
      "\n",
      "solved in Episode {} 960\n",
      "Total score (averaged over agents) this episode\t961:\t37.7840\tAverage Score:\t32.3206\ttime: 0:01:07.792892\n",
      "\n",
      "solved in Episode {} 961\n",
      "Total score (averaged over agents) this episode\t962:\t37.8680\tAverage Score:\t32.3687\ttime: 0:01:00.808727\n",
      "\n",
      "solved in Episode {} 962\n",
      "Total score (averaged over agents) this episode\t963:\t37.9825\tAverage Score:\t32.4331\ttime: 0:01:01.409733\n",
      "\n",
      "solved in Episode {} 963\n",
      "Total score (averaged over agents) this episode\t964:\t37.5180\tAverage Score:\t32.4788\ttime: 0:01:01.129240\n",
      "\n",
      "solved in Episode {} 964\n",
      "Total score (averaged over agents) this episode\t965:\t37.1535\tAverage Score:\t32.5088\ttime: 0:01:00.455655\n",
      "\n",
      "solved in Episode {} 965\n",
      "Total score (averaged over agents) this episode\t966:\t37.5595\tAverage Score:\t32.5573\ttime: 0:01:09.196297\n",
      "\n",
      "solved in Episode {} 966\n",
      "Total score (averaged over agents) this episode\t967:\t36.9665\tAverage Score:\t32.5807\ttime: 0:01:13.174114\n",
      "\n",
      "solved in Episode {} 967\n",
      "Total score (averaged over agents) this episode\t968:\t34.2740\tAverage Score:\t32.5652\ttime: 0:01:12.580875\n",
      "\n",
      "solved in Episode {} 968\n",
      "Total score (averaged over agents) this episode\t969:\t34.9750\tAverage Score:\t32.5654\ttime: 0:01:09.970648\n",
      "\n",
      "solved in Episode {} 969\n",
      "Total score (averaged over agents) this episode\t970:\t34.8265\tAverage Score:\t32.5543\ttime: 0:01:17.416464\n",
      "\n",
      "solved in Episode {} 970\n",
      "Total score (averaged over agents) this episode\t971:\t34.7770\tAverage Score:\t32.5421\ttime: 0:01:01.585555\n",
      "\n",
      "solved in Episode {} 971\n",
      "Total score (averaged over agents) this episode\t972:\t36.0545\tAverage Score:\t32.5527\ttime: 0:01:09.495043\n",
      "\n",
      "solved in Episode {} 972\n",
      "Total score (averaged over agents) this episode\t973:\t35.9040\tAverage Score:\t32.5639\ttime: 0:01:07.658893\n",
      "\n",
      "solved in Episode {} 973\n",
      "Total score (averaged over agents) this episode\t974:\t36.1045\tAverage Score:\t32.5659\ttime: 0:01:07.859110\n",
      "\n",
      "solved in Episode {} 974\n",
      "Total score (averaged over agents) this episode\t975:\t34.5200\tAverage Score:\t32.5893\ttime: 0:01:05.930392\n",
      "\n",
      "solved in Episode {} 975\n",
      "Total score (averaged over agents) this episode\t976:\t33.3940\tAverage Score:\t32.5639\ttime: 0:00:56.245176\n",
      "\n",
      "solved in Episode {} 976\n",
      "Total score (averaged over agents) this episode\t977:\t31.6170\tAverage Score:\t32.5476\ttime: 0:01:05.458396\n",
      "\n",
      "solved in Episode {} 977\n",
      "Total score (averaged over agents) this episode\t978:\t32.4935\tAverage Score:\t32.4959\ttime: 0:01:08.356243\n",
      "\n",
      "solved in Episode {} 978\n",
      "Total score (averaged over agents) this episode\t979:\t34.3935\tAverage Score:\t32.4664\ttime: 0:01:06.592329\n",
      "\n",
      "solved in Episode {} 979\n",
      "Total score (averaged over agents) this episode\t980:\t34.7015\tAverage Score:\t32.4390\ttime: 0:01:07.428386\n",
      "\n",
      "solved in Episode {} 980\n",
      "Total score (averaged over agents) this episode\t981:\t35.5925\tAverage Score:\t32.4217\ttime: 0:01:02.211962\n",
      "\n",
      "solved in Episode {} 981\n",
      "Total score (averaged over agents) this episode\t982:\t34.1270\tAverage Score:\t32.4025\ttime: 0:01:02.068690\n",
      "\n",
      "solved in Episode {} 982\n",
      "Total score (averaged over agents) this episode\t983:\t32.6995\tAverage Score:\t32.3557\ttime: 0:00:56.637568\n",
      "\n",
      "solved in Episode {} 983\n",
      "Total score (averaged over agents) this episode\t984:\t30.6340\tAverage Score:\t32.3312\ttime: 0:00:53.671411\n",
      "\n",
      "solved in Episode {} 984\n",
      "Total score (averaged over agents) this episode\t985:\t29.7095\tAverage Score:\t32.2827\ttime: 0:00:56.872693\n",
      "\n",
      "solved in Episode {} 985\n",
      "Total score (averaged over agents) this episode\t986:\t28.0285\tAverage Score:\t32.2313\ttime: 0:00:57.024806\n",
      "\n",
      "solved in Episode {} 986\n",
      "Total score (averaged over agents) this episode\t987:\t29.8905\tAverage Score:\t32.1807\ttime: 0:00:55.417259\n",
      "\n",
      "solved in Episode {} 987\n",
      "Total score (averaged over agents) this episode\t988:\t31.0470\tAverage Score:\t32.1292\ttime: 0:00:55.114532\n",
      "\n",
      "solved in Episode {} 988\n",
      "Total score (averaged over agents) this episode\t989:\t31.5790\tAverage Score:\t32.0913\ttime: 0:00:54.752553\n",
      "\n",
      "solved in Episode {} 989\n",
      "Total score (averaged over agents) this episode\t990:\t29.7725\tAverage Score:\t32.0554\ttime: 0:00:57.475771\n",
      "\n",
      "solved in Episode {} 990\n",
      "Total score (averaged over agents) this episode\t991:\t33.0275\tAverage Score:\t32.0377\ttime: 0:01:01.236204\n",
      "\n",
      "solved in Episode {} 991\n",
      "Total score (averaged over agents) this episode\t992:\t31.9105\tAverage Score:\t31.9911\ttime: 0:00:58.001712\n",
      "\n",
      "solved in Episode {} 992\n",
      "Total score (averaged over agents) this episode\t993:\t30.5490\tAverage Score:\t31.9419\ttime: 0:01:09.514702\n",
      "\n",
      "solved in Episode {} 993\n",
      "Total score (averaged over agents) this episode\t994:\t32.2495\tAverage Score:\t31.9130\ttime: 0:00:58.792896\n",
      "\n",
      "solved in Episode {} 994\n",
      "Total score (averaged over agents) this episode\t995:\t34.1880\tAverage Score:\t31.8922\ttime: 0:00:58.816012\n",
      "\n",
      "solved in Episode {} 995\n",
      "Total score (averaged over agents) this episode\t996:\t33.2920\tAverage Score:\t31.8545\ttime: 0:01:02.457741\n",
      "\n",
      "solved in Episode {} 996\n",
      "Total score (averaged over agents) this episode\t997:\t32.6200\tAverage Score:\t31.8011\ttime: 0:01:04.012805\n",
      "\n",
      "solved in Episode {} 997\n",
      "Total score (averaged over agents) this episode\t998:\t34.8505\tAverage Score:\t31.7814\ttime: 0:01:08.492807\n",
      "\n",
      "solved in Episode {} 998\n",
      "Total score (averaged over agents) this episode\t999:\t34.8445\tAverage Score:\t31.7841\ttime: 0:01:00.150062\n",
      "\n",
      "solved in Episode {} 999\n",
      "Total score (averaged over agents) this episode\t1000:\t31.2525\tAverage Score:\t31.7371\ttime: 0:01:03.488781\n",
      "Episode 1000\tAverage Score: 31.74\n",
      "\n",
      "solved in Episode {} 1000\n"
     ]
    }
   ],
   "source": [
    "\n",
    "episodes = 1000\n",
    "scores = []\n",
    "scores_window = deque(maxlen=100)\n",
    "avg_scores = []\n",
    "avg_scores.append(0)\n",
    "avg = []\n",
    "for episode in range(1, episodes+1): \n",
    "    env_info = env.reset(train_mode=True)[brain_name]     # reset the environment    \n",
    "    states = env_info.vector_observations                  # get the current state (for each agent)\n",
    "    agent.reset();\n",
    "    ep_scores = np.zeros(num_agents)                          # initialize the score (for each agent)\n",
    "    start = datetime.datetime.now()\n",
    "    while True:\n",
    "        actions = agent.act(states) # select an action (for each agent)\n",
    "        actions = np.clip(actions, -1, 1)                  # all actions between -1 and 1\n",
    "        env_info = env.step(actions)[brain_name]           # send all actions to tne environment\n",
    "        next_states = env_info.vector_observations         # get next state (for each agent)\n",
    "        rewards = env_info.rewards                        # get reward (for each agent)\n",
    "        dones = env_info.local_done                        # see if episode finished\n",
    "        ep_scores += env_info.rewards                         # update the score (for each agent)\n",
    "    \n",
    "        [agent.step(states[i], actions[i], rewards[i], next_states[i], dones[i]) for i in range(num_agents)]\n",
    "        \n",
    "        agent.step_learn()\n",
    "        \n",
    "    \n",
    "        states = next_states                               # roll over states to next time step\n",
    "        if np.any(dones):                                  # exit loop if episode finished\n",
    "            break\n",
    "    took = datetime.datetime.now() -start\n",
    "    scores.append(np.mean(ep_scores))\n",
    "    scores_window.append(np.mean(ep_scores))\n",
    "    avg_score = np.mean(scores_window)\n",
    "    print('Total score (averaged over agents) this episode\\t{}:\\t{:.4f}\\tAverage Score:\\t{:.4f}\\ttime: {:s}'.format(episode, np.mean(ep_scores), avg_score, str(took)))\n",
    "    \n",
    "    if episode % 100 == 0:        \n",
    "        print('\\rEpisode {}\\tAverage Score: {:.2f}'.format(episode,avg_score))\n",
    "        avg_scores.append(avg_score)\n",
    "        torch.save(agent.actor_local.state_dict(), 'checkpoint_{:d}_actor.pth'.format(episode))\n",
    "        torch.save(agent.critic_local.state_dict(), 'checkpoint_{:d}_critic.pth'.format(episode))\n",
    "    if avg_score >= 30.0:\n",
    "        print()\n",
    "        print('solved in Episode {}', episode)\n",
    "        torch.save(agent.actor_local.state_dict(), 'solved_{:d}_actor_local.pth'.format(episode))\n",
    "        torch.save(agent.critic_local.state_dict(), 'solved_{:d}_critic_local.pth'.format(episode))\n",
    "        \n",
    "torch.save(agent.actor_local.state_dict(), 'end_actor_local.pth')\n",
    "torch.save(agent.critic_local.state_dict(), 'end_critic_local.pth')\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "env.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# plot the scores\n",
    "fig = plt.figure(figsize=(16, 12))\n",
    "ax = fig.add_subplot(111)\n",
    "plt.plot(np.arange(len(scores)), scores)\n",
    "plt.plot(np.arange(len(scores)), 30*np.ones(len(scores)))\n",
    "plt.xlabel('Episode number')\n",
    "plt.ylabel('Score')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 2.842974936454557, 2.7039049395630137, 6.763404848826118, 9.449074788796715, 10.790829758806156, 10.366679768286645, 21.9465845094556, 36.37992418684531, 34.16415923637152, 31.737129290619865]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(avg_scores)\n",
    "fig = plt.figure(figsize=(16, 12))\n",
    "ax = fig.add_subplot(111)\n",
    "plt.plot(np.arange(len(avg_scores)), avg_scores)\n",
    "plt.plot(np.arange(len(avg_scores)), 30*np.ones(len(avg_scores)))\n",
    "plt.xlabel('100 Episodes')\n",
    "plt.ylabel('Avg Score')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "drlnd2",
   "language": "python",
   "name": "drlnd2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}