# Mean Field Multi-Agent Reinforcement Learning

*Source* · `src-yang-2018-mean-field-marl` · status: **n/a**

| field | value |
|---|---|
| kind | Peer-reviewed paper |
| authors | Yaodong Yang, Rui Luo, Minne Li, Ming Zhou, Weinan Zhang, Jun Wang |
| venue | ICML 2018 |
| date | 2018-02-15 |
| url | https://arxiv.org/abs/1802.05438 |
| arxiv | 1802.05438 |
| accessed | 2026-10-24 |
| notes | Each agent learns against the mean action of neighbors instead of all pairwise interactions; mixed cooperative-competitive battle games and Ising model. |

## Backlinks (computed)

**cited by:** [Mean field games and mean-field learning](../technique/mean-field-games.md)

## Citation

Yaodong Yang, Rui Luo, Minne Li, Ming Zhou, Weinan Zhang, Jun Wang (2018-02-15). *Mean Field Multi-Agent Reinforcement Learning*. ICML 2018 https://arxiv.org/abs/1802.05438

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Provenance: created in run `2026-10-24-techniques-sim-math`.