GAME-THEORETIC MODELS OF LEARNING PROCESSES

We studied population games. In particular, we focused on imitation dynamics, which rely on little information on the game. We developed a theory for the study of the asymtptic behavior of these population games, including deterministic and stochastic formualtions, application on networks, and on switching systems, Our body of works is summarized in the following publications: 

• Zino L., Como G., and Fagnani F., On Imitation Dynamics in Potential Population Games. Proceedings of the 56th IEEE Conference on Decision and Control, Dec 2017, Melbourne, Australia

• Zino L., Como G., and Fagnani F., On stochastic imitation dynamics in large-scale networks. Proceedings of the 17th European Control Conference, Jun 2018, Limassol, Cyprus

• Como G., Fagnani F., and Zino L., Imitation dynamics in population games on community networks. IEEE Transactions on Control of Network Systems, 8(1), 65–76, 2021

• Cunha R., Zino L., and Cao M., On imitation dynamics in population games with Markov switching. Proceedings of the 20th European Control Conference, Jun-Jul 2021, Rotterdam, The Netherlands

• Govaert A., Zino L., Tegling E., Population games on dynamic community networks. IEEE Control Systems Letters, 6, 2695–2700, 2022

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We studied generalized Nash equilibrium problems under a partial-decision information regime:

• B. Franci, F. Fabiani, and Zino L., Generalized Nash equilibrium problems under partial-decision information with biased agents. To appear in the Proceedings of the 63rd IEEE Conference on Decision and Control, 2024