Population games with replicator dynamics under event-triggered payoff provider and a demand response application

Journal Article (2023)
Author(s)

Juan Martinez-Piazuelo (Universitat Politecnica de Catalunya)

W. Ananduta (TU Delft - Team Sergio Grammatico)

Carlos Ocampo-Martinez (Universitat Politecnica de Catalunya)

Sergio Grammatico (TU Delft - Team Bart De Schutter, TU Delft - Team Sergio Grammatico)

Nicanor Quijano (Universidad de los Andes)

Research Group
Team Sergio Grammatico
Copyright
© 2023 Juan Martinez-Piazuelo, W. Ananduta, Carlos Ocampo-Martinez, S. Grammatico, Nicanor Quijano
DOI related publication
https://doi.org/10.1109/LCSYS.2023.3285532
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Juan Martinez-Piazuelo, W. Ananduta, Carlos Ocampo-Martinez, S. Grammatico, Nicanor Quijano
Research Group
Team Sergio Grammatico
Volume number
7
Pages (from-to)
3417-3422
Reuse Rights

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Abstract

We consider a large population of decision makers that choose their evolutionary strategies based on simple pairwise imitation rules. We describe such a dynamic process by the replicator dynamics. Differently from the available literature, where the payoffs signals are assumed to be updated continuously, we consider a more realistic scenario where they are updated occasionally. Our main technical contribution is to devise two event-triggered communication schemes with asymptotic convergence guarantees to a Nash equilibrium. Finally, we show how our proposed approach is applicable as an efficient distributed demand response mechanism.

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