This paper considers mean field games in a multiagent Markov decision process (MDP) framework. Each player has a continuum state and binary action. We analyze two stationary mean field games with discounted individual costs and long-run average individual costs, respectively. We show existence of a solution to the associated equation system, leading to threshold policies. Uniqueness is obtained under a product form cost and positive externalities.

Additional Metadata
Persistent URL dx.doi.org/10.1109/CDC.2017.8263638
Conference 56th IEEE Annual Conference on Decision and Control, CDC 2017
Citation
Huang, M, & Ma, Y. (Yan). (2018). Mean field stochastic games with binary actions: Stationary threshold policies. In 2017 IEEE 56th Annual Conference on Decision and Control, CDC 2017 (pp. 27–32). doi:10.1109/CDC.2017.8263638