Bayesian Nash equilibrium seeking for multi-agent incomplete-information aggregative games

Zhang, Hanzheng ; Qin, Huashu ; Chen, Guanpu

Kybernetika, Tome 59 (2023) no. 4, pp. 575-591

Abstract (VO)

In this paper, we consider a distributed Bayesian Nash equilibrium (BNE) seeking problem in incomplete-information aggregative games, which is a generalization of either Bayesian games or deterministic aggregative games. We handle the aggregation function to adapt to incomplete-information situations. Since the feasible strategies are infinite-dimensional functions and lie in a non-compact set, the continuity of types brings barriers to seeking equilibria. To this end, we discretize the continuous types and then prove that the equilibrium of the derived discretized model is an $\epsilon$-BNE. On this basis, we propose a distributed algorithm for an $\epsilon$-BNE and further prove its convergence.

Détail

DOI : 10.14736/kyb-2023-4-0575

Classification : 68W15, 91A27, 91A43
Keywords: aggregative games; Bayesian games; equilibrium approximation; distributed algorithms

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