Year: 2024
Type: conference-paper
Abstract: We consider a large population of learning agents noncooperatively selecting strategies from a common set, influencing the dynamics of an exogenous system (ES) we seek to stabilize at a desired equilibrium. Our approach is to design a dynamic payoff mechanism capable of shaping the population’s strategy profile, thus affecting the ES’s state, by offering incentives for specific strategies within budget limits. Employing system-theoretic passivity concepts, we establish conditions under which a payoff mechanism can be systematically constructed to ensure the global asymptotic stability of the ES’s equilibrium. In comparison to previous approaches originally studied in the context of the so-called epidemic population games, the method proposed here allows for more realistic epidemic models and other types of ESs, such as predator-prey dynamics. The stability of the equilibrium is established with the support of a Lyapunov function, which provides useful bounds on the transient states.
Language: English
Topic: Game Theory and Applications
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
Awards: Collaborative Research: CPS: Medium: Population Games for Cyber-Physical Systems: New Theory with Tools for Transportation Management under Extreme Demand, Collaborative Research: CPS: Medium: ASTrA: Automated Synthesis for Trustworthy Autonomous Utility Services, Collaborative Research:CPS Medium: Population Games for Cyber-Physical Systems: New Theory with Tools for Transportation Management under Extreme Demand, G778008054
OpenAlex ID: W4407950324