3D Packing with Deep Reinforcement Learning using Unity ML-Agents (AI)

A collection of my implemented RL agents for games like Pacman, Pong, SpaceInvaders, Frozenlake, Taxi, Pixelcopter, Pyramids and a lot more by implementing various DRL algorithms using gym, unity-ml, pygame, sb3, rl-zoo and pandagym libraries. To see more advanced & interesting agents, please visit below link:

Multi agent PPO implementation in Pytorch for Unity ML Agents environments.

Small Reinforcement Learning Framework

심층강화학습기반 디지털 트윈 환경에서의 자율주행 연구

This repository contains a University project on the Reinforcement Learning subject, in which we develop a bot able to use some of Brandon Sanderson's Mistborn fantasy book's abilities in order to reach a goal in a 2D platform environment.

Proximal Policy Optimization(PPO) with Intrinsic Curiosity Module(ICM) on Pyramid env, Unity ML

Code for generating data in ICML 2020 paper "PackIt: A Virtual Environment for Geometric Planning"

Code for reproducing results in ICML 2020 paper "PackIt: A Virtual Environment for Geometric Planning"

Pong AI - Reinforcement Learning Agent for Playing Pong

Age of war clone made in unity in order to speed up the neat algorithm training process. The values are extracted from the original game. It Communicates with a python script

RL Algorithms with examples in Python / Pytorch / Unity ML agents

Udacity's Reinforcement Learning Project 1

Deep Q-Learning Agent mastering the Unity Banana Collector environment! — Udacity Deep RL Nanodegree Project

A pair of reinforcement learning agents that can play tennis 🎾 — Udacity Deep RL Nanodegree Project

Usage of Unity ML-Agents train two agents to play tennis

Using MADDPG for solving Multi Agent Based Unity Environment

Some of my solutions of the exercises and all my projects of the Udacity Deep Reinforcement Learning Nanodegree https://www.udacity.com/course/deep-reinforcement-learning-nanodegree--nd893

This is a reinforcement learning project in unity ml-agents environment. An agent is trained to navigate (and collect bananas!) in a large, square world. The Agent is a DQN written in pytorch.

A collection of algorithms for Deep Reinforcement Learning (DRL). Algorithms covered include Value-Based, Policy-Based and Actor-Critic Methods.