Mean field theory is decision making under uncertainty approach which responds to the agregate actions of many agents rather than agents individually.
Our Papers on Mean Field Theory
- Mean Field MARLDecentralized Mean Field GamesIn Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-2022). Virtual. Feb, 2022.
- PO-MFRLPartially Observable Mean Field Reinforcement LearningIn Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS). International Foundation for Autonomous Agents and Multiagent Systems, London, United Kingdom. May, 2021.