Publication

Relative Best Response Dynamics in Finite and Convex Network Games

Govaert, A., Cenedese, C., Grammatico, S. & Cao, M., 12-Mar-2020, Proceedings of the 58th IEEE Conference on Decision and Control. IEEE, p. 3134-3139

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Copy link to clipboard

Documents

  • Relative Best Response Dynamics in finite and convex Network Games

    Final publisher's version, 359 KB, PDF document

    Request copy

DOI

Motivated by theoretical and experimental economics, we propose novel evolutionary dynamics for games on networks, called the h-Relative Best Response (h–RBR) dynamics, that mixes the relative performance considerations of imitation dynamics with the rationality of best responses. Under such a class of dynamics, the players optimize their payoffs over the set of strategies employed by a time–varying subset of their neighbors. As such, the h-RBR dynamics share the defining non–innovative characteristic of imitation based dynamics and can lead to equilibria that differ from classic Nash equilibria. We study the asymptotic behavior of the h–RBR dynamics for both finite and convex games in which the strategy spaces are discrete and compact, respectively, and provide preliminary sufficient conditions for finite–time convergence to a generalized Nash equilibrium.
Original languageEnglish
Title of host publicationProceedings of the 58th IEEE Conference on Decision and Control
PublisherIEEE
Pages3134-3139
ISBN (Print)978-1-7281-1398-2
Publication statusPublished - 12-Mar-2020
Event58th Conference on Decision and Control (CDC2019) - Nice, France
Duration: 11-Dec-201913-Dec-2019

Conference

Conference58th Conference on Decision and Control (CDC2019)
CountryFrance
CityNice
Period11/12/201913/12/2019

Event

58th Conference on Decision and Control (CDC2019)

11/12/201913/12/2019

Nice, France

Event: Conference

ID: 109250413