Nash equilibria in concurrent games with lexicographic preferences

Julian Gutierrez, Aniello Murano, Giuseppe Perelli, Sasha Rubin, Michael Wooldridge

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

12 Citations (Scopus)

Abstract

We study concurrent games with finite-memory strategies where players are given a Büchi and a mean-payoff objective, which are related by a lexicographic order: a player first prefers to satisfy its Büchi objective, and then prefers to minimise costs, which are given by a mean-payoff function. In particular, we show that deciding the existence of a strict Nash equilibrium in such games is decidable, even if players' deviations are implemented as infinite memory strategies.

Original languageEnglish
Title of host publicationProceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
EditorsCarles Sierra
Place of PublicationMarina del Rey CA USA
PublisherAssociation for the Advancement of Artificial Intelligence (AAAI)
Pages1067-1073
Number of pages7
ISBN (Electronic)9780999241103
ISBN (Print)9780999241110
DOIs
Publication statusPublished - 2017
Externally publishedYes
EventInternational Joint Conference on Artificial Intelligence 2017 - Melbourne, Australia
Duration: 19 Aug 201725 Aug 2017
Conference number: 26th
https://ijcai-17.org/

Conference

ConferenceInternational Joint Conference on Artificial Intelligence 2017
Abbreviated titleIJCAI 2017
CountryAustralia
CityMelbourne
Period19/08/1725/08/17
Internet address

Keywords

  • Knowledge Representation
  • Reasoning, and Logic
  • Game Theory
  • Agent-based and Multi-agent Systems
  • Formal verification, validation and synthesis

Cite this

Gutierrez, J., Murano, A., Perelli, G., Rubin, S., & Wooldridge, M. (2017). Nash equilibria in concurrent games with lexicographic preferences. In C. Sierra (Ed.), Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (pp. 1067-1073). Association for the Advancement of Artificial Intelligence (AAAI). https://doi.org/10.24963/ijcai.2017/148