openai/multiagent-particle-envs

Health v2 · maintenance only

Flags: no_releases archived

Adoption not part of the score

2774 stars · 820 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A simple multi-agent particle world environment with continuous observations and discrete actions, used in the paper 'Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments'. It provides Gym-like environments with customizable scenarios for multi-agent reinforcement learning research.

Use cases

• train multi-agent reinforcement learning policies
• reproduce the MADDPG paper experiments
• create custom cooperative-competitive multi-agent scenarios
• visually inspect agent behaviors in a particle world
• benchmark multi-agent algorithms on simple environments

When to choose

• reproducing the Multi-Agent Actor-Critic paper
• prototyping multi-agent RL algorithms on lightweight environments
• teaching multi-agent reinforcement learning concepts

When to avoid

• you need maintained, pip-installable environments with modern Python support (use PettingZoo instead)
• you need photorealistic or complex 3D simulations
• you need production-ready software

Facets

library · maturity abandoned

simulation machine-learning reinforcement-learning reinforcement-learning machine-learning simulation python cross-platform multi-agent gym-environments particle-environment research-code archived cooperative-competitive marl research

Member repositories

For agents

markdown · JSON · MCP: product_card(name="openai/multiagent-particle-envs")