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Reinforcement Learning with openAI gym/gymnasium, MineRL and Unity

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Reinforcement Learning Projects

This repository hosts diffrent reinforcement learning implementations across diverse environments and algorithms.

Projects

1. OpenAI Gym Dino DQN

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.

2. MineRL PPO Agent

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.

3. ML-Agents Unity

Trains a 2D agent in a Unity ML-Agents environment to navigate to targets.

  • Dependencies: numpy, torch,mlagents, pyyaml, Unity Editor.

Prerequisites

  • Python 3.8+
  • pip for package installation.

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Reinforcement Learning with openAI gym/gymnasium, MineRL and Unity

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