# Replicable-MARL/MARLlib

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

Repository: https://github.com/Replicable-MARL/MARLlib
Canonical: https://ross.abutalabs.com/products/marllib
Homepage: https://marllib.readthedocs.io
Language: Python
License: MIT
License Family: permissive
Topics: multi-agent-reinforcement-learning, ray, rllib, pytorch, deep-reinforcement-learning
Last push: 2024-11-28T07:04:07+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 1723, "days_push": 643, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1345, forks 198 (observed 2026-08-28T04:04:27.355039+00:00)

## What it is
MARLlib is a unified multi-agent reinforcement learning library built on Ray and RLlib with PyTorch, providing implementations of many MARL algorithms and integration with numerous multi-agent environments. It offers a unified API for training, tuning, and benchmarking MARL agents across cooperative, competitive, and mixed settings.

## Use cases
- train multi-agent reinforcement learning agents
- benchmark MARL algorithms across environments
- run cooperative and competitive multi-agent RL experiments
- use PettingZoo environments with RLlib
- reproduce multi-agent RL research results
- compare centralized vs decentralized training approaches

## When to choose
- you need many MARL algorithms under one unified API
- you want Ray/RLlib scalability for multi-agent training
- you want built-in support for popular multi-agent environments like MPE, SMAC, and PettingZoo

## When to avoid
- you need single-agent RL only
- you require the latest RLlib versions or active feature development
- you need lightweight training without Ray dependencies

## Facets
- artifact type: library
- maturity: maintenance
- function: reinforcement-learning, machine-learning, sdk
- domain: reinforcement-learning, machine-learning, artificial-intelligence
- platform: python
- tags: multi-agent-reinforcement-learning, rllib, ray, pytorch, marl-algorithms, pettingzoo, research-library, research, gpu, linux, macos

## Member repositories
- Replicable-MARL/MARLlib (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:27.355039+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:42:44.322505+00:00, confidence not recorded.
  - readme: https://github.com/Replicable-MARL/MARLlib (fetched 2026-08-28T04:04:27.355039+00:00, sha 8e72e9d37852)
- Data as of 2026-08-30T08:39:29.467469+00:00.