Incentive Designs for Learning Agents to Stabilize Coupled Exogenous Systems
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866910603094786048 |
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| author | Certório, Jair Martins, Nuno C. La, Richard J. Arcak, Murat |
| author_facet | Certório, Jair Martins, Nuno C. La, Richard J. Arcak, Murat |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2403_18164 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Incentive Designs for Learning Agents to Stabilize Coupled Exogenous Systems Certório, Jair Martins, Nuno C. La, Richard J. Arcak, Murat Systems and Control Dynamical Systems Optimization and Control 92D10, 92D25 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. |
| title | Incentive Designs for Learning Agents to Stabilize Coupled Exogenous Systems |
| topic | Systems and Control Dynamical Systems Optimization and Control 92D10, 92D25 |
| url | https://arxiv.org/abs/2403.18164 |