Scaling up Multi-agent Reinforcement Learning with Mean Field Games and Vice-versa. (Mise à l'échelle de l'apprentissage par renforcement multi-agent grâce aux jeux à champ moyen et vice-versa).

[BibT_eX]

[DOI]

Sarah Perrin

PhD thesis, 2022

Learning Correlated Equilibria in Mean-Field Games.

[BibT_eX]

[DOI]

CoRR, 2022

Learning Mean Field Games: A Survey.

[BibT_eX]

[DOI]

CoRR, 2022

Scalable Deep Reinforcement Learning Algorithms for Mean Field Games.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Scaling Mean Field Games by Online Mirror Descent.

[BibT_eX]

[DOI]

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Concave Utility Reinforcement Learning: The Mean-field Game Viewpoint.

[BibT_eX]

[DOI]

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Solving N-Player Dynamic Routing Games with Congestion: A Mean-Field Approach.

[BibT_eX]

[DOI]

Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Generalization in Mean Field Games by Learning Master Policies.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Scaling up Mean Field Games with Online Mirror Descent.

[BibT_eX]

[DOI]

CoRR, 2021

Mean Field Games Flock! The Reinforcement Learning Way.

[BibT_eX]

[DOI]

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

2020

Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Sarah Perrin

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