multi-agent-reinforcement-learning

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

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

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

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

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

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

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

Unified Reinforcement Learning Framework

BenchMARL is a library for benchmarking Multi-Agent Reinforcement Learning (MARL). BenchMARL allows to quickly compare different MARL algorithms, tasks, and models while being systematically grounded in its two core tenets: reproducibility and standardization.

RLAnything (ICML 2026) & AutoTool (ICML 2026), DemyAgent: Open-Source RL for LLMs and Agentic Scenarios

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.

[ICLR 2026] A Framework for LLM-based Multi-Agent Reinforced Training and Inference