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Autores principales: Luque-Cerpa, Alejandro, Gutiérrez-Naranjo, Miguel A.
Formato: Preprint
Publicado: 2024
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Acceso en línea:https://arxiv.org/abs/2404.17671
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author Luque-Cerpa, Alejandro
Gutiérrez-Naranjo, Miguel A.
author_facet Luque-Cerpa, Alejandro
Gutiérrez-Naranjo, Miguel A.
contents In Evolutionary Game Theory (EGT), a population reaches a Nash equilibrium when none of the agents can improve its objective by solely changing its strategy on its own. Roughly speaking, this equilibrium is a protection against betrayal. Generalized Nash Equilibrium (GNE) is a more complex version of this idea with important implications in real-life problems in economics, wireless communication, the electricity market, or engineering among other areas. In this paper, we propose a first approach to GNE with Membrane Computing techniques and show how GNE problems can be modeled with P systems, bridging both areas and opening a door for a flow of problems and solutions in both directions.
format Preprint
id arxiv_https___arxiv_org_abs_2404_17671
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Membrane Computing Approach to the Generalized Nash Equilibrium
Luque-Cerpa, Alejandro
Gutiérrez-Naranjo, Miguel A.
Computer Science and Game Theory
In Evolutionary Game Theory (EGT), a population reaches a Nash equilibrium when none of the agents can improve its objective by solely changing its strategy on its own. Roughly speaking, this equilibrium is a protection against betrayal. Generalized Nash Equilibrium (GNE) is a more complex version of this idea with important implications in real-life problems in economics, wireless communication, the electricity market, or engineering among other areas. In this paper, we propose a first approach to GNE with Membrane Computing techniques and show how GNE problems can be modeled with P systems, bridging both areas and opening a door for a flow of problems and solutions in both directions.
title A Membrane Computing Approach to the Generalized Nash Equilibrium
topic Computer Science and Game Theory
url https://arxiv.org/abs/2404.17671