Current browse context:
eess.SY
Change to browse by:
References & Citations
Electrical Engineering and Systems Science > Systems and Control
Title: Incentive Designs for Learning Agents to Stabilize Coupled Exogenous Systems
(Submitted on 27 Mar 2024)
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 stabilization 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 ES, such as predator-prey dynamics. Stabilization is established with the support of a Lyapunov function, which provides useful bounds on the transients.
Link back to: arXiv, form interface, contact.