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.

Train a system of DeepRL agents to demonstrate collaboration or cooperation on a complex task.

Project 2 of Udacity's Deep Reinforcement Learning Nanodegree Program

My solutions to the projects within the Udacity Deep Reinforcement Learning Nanodegree.

Udacity Deep Reinforcement Learning Nanodegree - Project 1: Navigation

First steps in ML-Agents and Unity 🤖

Navigation project environment from Unity ML-Agents

심층강화학습기반 디지털 트윈 환경에서의 자율주행 연구

Implementation of the DDPG algorithm to solve Continuous Control Reacher Environment

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

AI based Massive Multiplayer Online Simulation

Reinforcement learning futbolito scenario trained with Unity ML Agents.

Project 1 of Udacity's Deep Reinforcement Learning Nanodegree Program

In this repo, I train Q-Learning based agent to navigate the large square world and collect bananas

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:

Udacity's Reinforcement Learning Project 1

Project 3 of Udacity's Deep Reinforcement Learning Nanodegree Program

Small Reinforcement Learning Framework

a deep reinforcement learning project for which an agent had to learn how to control 20 robotic arms to reach moving targets

Pong AI - Reinforcement Learning Agent for Playing Pong