Reducing Stochastic Games to Semidefinite Programming

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

Abstract

We present a polynomial-time reduction from max-average constraints to the feasibility problem for semidefinite programs. This shows that Condon’s simple stochastic games, stochastic mean payoff games, and in particular mean payoff games and parity games can all be reduced to semidefinite programming.

Details

Original languageEnglish
Title of host publication52nd International Colloquium on Automata, Languages, and Programming, ICALP 2025
EditorsKeren Censor-Hillel, Fabrizio Grandoni, Joel Ouaknine, Gabriele Puppis
PublisherSchloss Dagstuhl- Leibniz-Zentrum für Informatik GmbH, Dagstuhl Publishing
Number of pages15
ISBN (electronic)9783959773720
Publication statusPublished - 30 Jun 2025
Peer-reviewedYes

Publication series

SeriesLeibniz International Proceedings in Informatics, LIPIcs
Volume334
ISSN1868-8969

Conference

Title52nd EATCS International Colloquium on Automata, Languages, and Programming
Abbreviated titleICALP 2025
Conference number52
Duration8 - 11 July 2025
Website
LocationAarhus University
CityAarhus
CountryDenmark

External IDs

ORCID /0000-0001-8228-3611/work/208071917

Keywords

ASJC Scopus subject areas

Keywords

  • max-atom problem, max-average constraints, Mean-payoff games, semidefinite programming, stochastic games