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Dynamic Interventions With Limited Knowledge in Network Games
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DOI：10.1109/TCNS.2023.3333400.png)
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摘要
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This article studies the problem of intervention design for steering the actions of noncooperative players in quadratic network games to the social optimum. The players choose their actions with the aim of maximizing their individual payoff functions, while a central regulator uses interventions to modify their marginal returns and maximize the social welfare function. This work builds on the key observation that the solution to the steering problem depends on the knowledge of the regulator on the players' parameters and the underlying network. We therefore consider different scenarios based on limited knowledge and propose suitable static, dynamic, and adaptive intervention protocols. We formally prove convergence to the social optimum under the proposed mechanisms. We demonstrate our theoretical findings on a case study of Cournot competition with differentiated goods.
Keyword:
Regulators
Games
Protocols
Optimized production technology
Pricing
Convergence
Behavioral sciences
Economic networks
game theory
networked control systems
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5
论文数:
1.7K
被引数:
5.8K
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