A car soccer environment inspired by Rocket League for deep reinforcement learning experiments in an adversarial self-play setting.

Learn to create agents in Unity ML using Deep Reinforcement Learning with Tensorflow.

Samples for TensorFlow binding for .NET by Lost Tech

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

Proximal Policy Optimization with Beta distribution - uses multi agent Unity ML Tennis

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

Learning Continuous Control in Deep Reinforcement Learning

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

Continuous Control with deep reinforcement learning where the agent must reach a moving ball with a double jointed arm

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

Train an agent using RL to navigate (and collect bananas) in a large, square world

A self driving car created using Unity ML-Agents

In this repo, I implement deep deterministic policy gradients and multi-agent deep deterministic poilicy gradients to solve the Tennis enironment (Unity ML-Agents)

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

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

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

Project 3 of Udacity Deep Reinforcement Learning Nanodegree

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