An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities

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

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.

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

ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs.

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation net…

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

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

Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch

Efficient Large-Scale Fleet Management via Multi-Agent Deep Reinforcement Learning

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:

Multi-Robot Warehouse (RWARE): A multi-agent reinforcement learning environment

A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm

DI-engine docs (Chinese and English)

Unified Reinforcement Learning Framework

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 of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

This repository is for an open-source environment for multi-agent active voltage control on power distribution networks (MAPDN).

This is a framework for the research on multi-agent reinforcement learning and the implementation of the experiments in the paper titled by ''Shapley Q-value: A Local Reward Approach to Solve Global Reward Games''.

Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.