PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.

MARS is shortened for Multi-Agent Research Studio, a library for mulit-agent reinforcement learning research.

One repository is all that is necessary for Multi-agent Reinforcement Learning (MARL)

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKT…

A collection of multi agent environments based on OpenAI gym.

Level-based Foraging (LBF): A multi-agent environment for RL

Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II

Multiagent Reinforcement Learning Research Project

🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX

A toolkit for reproducible reinforcement learning research.

HandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.

Python Multi-Agent Reinforcement Learning framework

Implementation of Multi-Game Decision Transformers in PyTorch

A curated list of Decision Transformer resources (continually updated)

Deep Transformer Q-Networks for Partially Observable Reinforcement Learning

VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set …

Reinforcement Learning Algorithm Package & PuckWorld, GridWorld Gym environments

A PyTorch library for building deep reinforcement learning agents.

2D Driving Simulator

OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

A pytorch implementation of MADDPG (multi-agent deep deterministic policy gradient)

Simple and easily configurable grid world environments for reinforcement learning

Lightweight multi-agent gridworld Gym environment

Code for "Actor-Attention-Critic for Multi-Agent Reinforcement Learning" ICML 2019

PyTorch implements multi-agent reinforcement learning algorithms, including QMIX, Independent PPO, Centralized PPO, Grid Wise Control, Grid Wise Control+PPO, Grid Wise Control+DDPG.

A web based platform for collecting human actions in reinforcement learning environments

xingtian is a componentized library for the development and verification of reinforcement learning algorithms

RL starter files in order to immediately train, visualize and evaluate an agent without writing any line of code

Multi-Agent Connected Autonomous Driving (MACAD) Gym environments for Deep RL. Code for the paper presented in the Machine Learning for Autonomous Driving Workshop at NeurIPS 2019: