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

DOI10.14736/kyb-2023-4-0575arXiv2301.04376MaRDI QIDQ6137157

Huashu Qin, Guanpu Chen, Unnamed Author

Publication date: 18 January 2024

Published in: Kybernetika (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2301.04376

zbMATH Keywords

aggregative gamesdistributed algorithmsBayesian gamesequilibrium approximation

Mathematics Subject Classification ID

Games involving graphs (91A43) Distributed algorithms (68W15) Games with incomplete information, Bayesian games (91A27)

Cites Work

• Bayesian Nash equilibrium and variational inequalities
• Computing pure Bayesian-Nash equilibria in games with finite actions and continuous types
• Distributed Nash equilibrium seeking for aggregative games with coupled constraints
• On the existence of equilibria to Bayesian games with non-finite type and action spaces
• Distributed algorithm for \(\varepsilon \)-generalized Nash equilibria with uncertain coupled constraints
• Distributed Algorithms for Aggregative Games on Graphs
• Distributional Strategies for Games with Incomplete Information
• Constrained Consensus and Optimization in Multi-Agent Networks
• Learning implicit information in Bayesian games with knowledge transfer
• Existence and Approximation of Continuous Bayesian Nash Equilibria in Games with Continuous Type and Action Spaces
• Games with Incomplete Information Played by “Bayesian” Players, I–III Part I. The Basic Model
• A Linearly Convergent Distributed Nash Equilibrium Seeking Algorithm for Aggregative Games

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