Reinforcement Learning · advanced · concept 185 of 311 · Updated Nov 4, 2026
Multi-Agent Reinforcement Learning
Multiple agents learning simultaneously in a shared environment, they can cooperate, compete, or both. Adds complexity: each agent's optimal strategy depends on what others do.
Top AI contributors on this
- Demis HassabisGoogle DeepMind (chair) / Isomorphic Labs
- Pieter AbbeelAmazon / UC Berkeley
- David SilverIneffable Intelligence / UCL
- John SchulmanThinking Machines Lab
- Sergey LevineUC Berkeley / Physical Intelligence
- Chelsea FinnStanford University / Physical Intelligence
Key terms
Nash equilibriumCooperativeCompetitiveSelf-play
Learn these first
Videos
▶ Multi-Agent Hide and Seek ↗
OpenAI · YouTube
▶ Multi Agent Systems Explained: How AI Agents & LLMs Work Together ↗
IBM Technology · YouTube
Guides and articles
Introduction · Hugging Face ↗
Hugging Face
Courses, papers, and more