This is the official implementation of Multi-Agent PPO (MAPPO).

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

Concise pytorch implements of MARL algorithms, including MAPPO, MADDPG, MATD3, QMIX and VDN.

MARLToolkit: The Multi-Agent Rainforcement Learning Toolkit. Include implementation of MAPPO, MADDPG, QMIX, VDN, COMA, IPPO, QTRAN, MAT...

A Simple, Distributed and Asynchronous Multi-Agent Reinforcement Learning Framework for Google Research Football AI.

Multi-agent PPO with noise (97% win rates on Hard scenarios of SMAC)

无人机动态覆盖控制；1. 实现了一个无人机点覆盖环境；2. 给出了无人机连通保持规则；3. 给出了基于MARL的控制算法

🎾 Multi-Agent Proximal Policy Optimization approach to a competitive reinforcement learning problem

General-Purpose Reinforcement Learning

RLToolkit is a flexible and high-efficient reinforcement learning framework. Include implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

Engineer-To-Order (ETO) Graph Neural Scheduling (GNS) Project

Implementation of a Civilization-like game used to study country growth in a competitive environment while accounting for environmental impact, with a Reinforcement Learning approach.

Multi agent reinforcement learning: PyTorch implementations of several algorithms for Multi Agent domains

Pytorch implementation of MAPPO algo in CleanRL style

Capturing the Flag (CTF) Multi-Agent Reinforcement Learning (MARL) in CTF game environment. The project evaluates different approaches like Independent Q-Learning (IQL) and Multi-Agent Proximal Policy Optimization (MAPPO) for cooperative and competitive agent interactions in a grid-world environment.