This repository hosts diffrent reinforcement learning implementations across diverse environments and algorithms.
Trains a Deep Q-Network (DQN) agent to play a Pygame-based Chrome Dinosaur game. The agent learns to jump obstacles using visual input and reward feedback. Uses gymnasium
a fork of openAI Gym
framework.
- Dependencies:
numpy
,torch
,pygame
,gymnasium
,matplotlib
.
Implements a Proximal Policy Optimization (PPO) agent in Minecraft (MineRL
environment) that performs gathering resources and lighting campfires tasks.
- Dependencies:
numpy
,torch
,minerl
,gym
,tqdm
.
Trains a 2D agent in a Unity ML-Agents environment to navigate to targets.
- Dependencies:
numpy
,torch
,mlagents
,pyyaml
, Unity Editor.
- Python 3.8+
pip
for package installation.