{"repo":"legalaspro/marl-ppo-suite","free":true,"listed":false,"github":"https://github.com/legalaspro/marl-ppo-suite","clone":"git clone https://github.com/legalaspro/marl-ppo-suite.git","description":"Clean, documented implementations of PPO-based algorithms for cooperative multi-agent reinforcement learning, focusing on SMAC environments. Features MLP and RNN-based MAPPO and HAPPO with various techniques.","language":"Python","stars":16,"topics":["mappo","multiagent-learning","multiagent-reinforcement-learning","multiagents","pytorch","reinforcement-learning-algorithms","rnn-gru","rnn-pytorch","smac","starcraft2"],"license":"MIT","category":"machine-learning","readme_excerpt":"Multi-Agent PPO Algorithms MAPPO vs HAPPO performance comparison on SMACv2 zerg 10 vs 10 (left) and zerg 5 vs 5 (right) maps A collection of clean, documented, and straightforward implementations of PPO-based algorithms for cooperative multi-agent reinforcement learning, with a focus on the StarCraft Multi-Agent Challenge (SMAC) environment. The implementations include MAPPO (Multi-Agent PPO) based on the paper \"The Surprising Effectiveness of PPO in Cooperative Multi-Agent Games\" and HAPPO (Heterogeneous-Agent PPO) based on the paper \"Heterogeneous-Agent Proximal Policy Optimization\". Currently implemented: - MAPPO : Multi-Agent PPO with both MLP and RNN networks - Light MAPPO : Lightweight single-environment implementation with MLP networks - Light RNN MAPPO : Lightweight single-environment implementation with RNN networks - Vectorized MAPPO : Full implementation with support for parallel environments - HAPPO : Heterogeneous-Agent PPO with agent-specific policies and vectorized environment support Both MAPPO and HAPPO support: - Vectorized environments using SubprocVecEnv and DummyVecEnv - Recurrent networks for handling partial observability - Various normalization techniques Supported environments: - SMACv1 : Original StarCraft Multi-Agent Challenge environment - SMACv2 : Next generation SMAC with enhanced capabilities and team compositions Project Overview This project began as a reimplementation of MAPPO (Multi-Agent Proximal Policy Optimization) with a focus on clarity","default_branch":null,"files":null,"tree":[],"storefront":"/r/legalaspro","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/legalaspro/marl-ppo-suite/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}