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Sequential Decomposition of Discrete-Time Mean-Field Games.
- Source :
- Dynamic Games & Applications; Jul2024, Vol. 14 Issue 3, p697-715, 19p
- Publication Year :
- 2024
-
Abstract
- We consider both finite- and infinite-horizon discounted mean-field games where there is a large population of homogeneous players sequentially making strategic decisions, and each player is affected by other players through an aggregate population state. Each player has a private type that only she observes and all players commonly observe a mean-field population state which represents the empirical distribution of other players' types. Mean-field equilibrium (MFE) in such games is defined as solution of coupled Bellman dynamic programming backward equation and Fokker–Planck forward equation, where a player's strategy in an MFE depends on both, her private type and current population state. In this paper, we present a novel backward recursive algorithm to compute all MFEs of the game. Each step in this algorithm consists of solving a fixed-point equation. We provide sufficient conditions that guarantee the existence of this fixed-point equation for each time t. Using this algorithm, we study versions of security problem in cyber-physical system where infected nodes put negative externality on the system, and each node makes a decision to get vaccinated. We numerically compute MFE of the game. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 21530785
- Volume :
- 14
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Dynamic Games & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 177673919
- Full Text :
- https://doi.org/10.1007/s13235-023-00507-w