openai/maddpg
Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments" observed · 2026-08-28
Health v2 · maintenance only
10/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases archived
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3135
- days_rel: n/a
- days_push: 884
- n_releases_24m: 0
Adoption not part of the score
1981 stars · 534 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Reference implementation of the MADDPG (Multi-Agent Deep Deterministic Policy Gradient) algorithm from OpenAI's paper on mixed cooperative-competitive multi-agent environments. It is a Python library designed to train agents in the Multi-Agent Particle Environments (MPE) using TensorFlow.
Use cases
- reproduce the MADDPG paper results
- train multi-agent reinforcement learning policies
- compare MADDPG against DDPG in cooperative-competitive settings
- experiment with multi-agent particle environments
- study centralized training with decentralized execution
When to choose
- you need the original reference implementation of MADDPG for research or study
- you want to train agents in OpenAI's Multi-Agent Particle Environments
- you are comparing multi-agent actor-critic algorithms
When to avoid
- you need a maintained library with modern TensorFlow or PyTorch support
- you want production-ready multi-agent RL tooling
- you need up-to-date dependencies or bug fixes
Facets
library · maturity abandoned
machine-learning reinforcement-learning machine-learning artificial-intelligence python maddpg multi-agent actor-critic deep-learning paper-code openai mpe research
1 source
- readme: https://github.com/openai/maddpg · fetched 2026-08-28 · a267b6be22a9
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| openai/maddpg | main | 10 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem