Repo for the Deep Reinforcement Learning Nanodegree program

Obstacle Tower Environment

Reinforcement Learning Algorithms Based on PyTorch

Various examples of ml-agents while teaching concepts about it in YouTube

UAV Logistics Environment for Multi-Agent Reinforcement Learning / Unity ML-Agents / Unity 3D

Animal-AI supports interdisciplinary research to help better understand human, animal, and artificial cognition.

A simple example of how to implement vector based DQN using PyTorch and a ML-Agents environment

An simple, reliable, and minimal implementation of the AI CoScientist Paper from Google "Towards an AI co-scientist" with Swarms Framework

Showcase environment for ML-Agents

A Complete Open Source Agent AI Framework For Unity

Train reinforcement learning agent using ML-Agents with Google Colab.

Repository for slides & codes of RL Korea Bootcamp

Research into Assault Course for training Active Ragdolls (using MujocoUnity+ml_agents)

A Self Play reinforcement learning Agent learns to play TicTacToe using the ML-Agents Framework in Unity.

Official implementation of paper "CityLearn: Diverse Real-World Environments for Sample-Efficient Navigation Policy Learning" by M. Chancán (ICRA 2020) https://doi.org/10.1109/ICRA40945.2020.9197336

A simple example of how to implement vector based DDPG for MARL tasks using PyTorch and a ML-Agents environment.

Motorcycle Racing made with Unity Machine Learning Agents

The Mayan Adventure is an open-source reinforcement learning environment for Unity ML-Agents. In this environment, you train your agent (Indie) to find the golden statue in this dangerous environment full of traps.

Research into controllers for 2d and 3d Active Ragdolls (using MujocoUnity+ml_agents)

This repository documents my journey to become a Machine Learning Engineer. It contains the list of projects undertaken, books read, courses pursued and almost everything I did in the process. So follow along or diverge to you own path, each way, I believe this will add value to any data professional / enthusiast.