CHEN, Taolue, Vojtěch FOREJT, Marta KWIATKOWSKA, Aistis SIMAITIS and Clemens WILTSCHE. On Stochastic Games with Multiple Objectives. In Krishnendu Chatterjee and Jiri Sgall. Proc. 38th International Symposium on Mathematical Foundations of Computer Science (MFCS'13). Berlin, Heidelberg: Springer, 2013, p. 266-277. ISBN 978-3-642-40312-5. Available from: https://dx.doi.org/10.1007/978-3-642-40313-2_25.
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Basic information
Original name On Stochastic Games with Multiple Objectives
Authors CHEN, Taolue (156 China), Vojtěch FOREJT (203 Czech Republic, guarantor, belonging to the institution), Marta KWIATKOWSKA (826 United Kingdom of Great Britain and Northern Ireland), Aistis SIMAITIS (440 Lithuania) and Clemens WILTSCHE (40 Austria).
Edition Berlin, Heidelberg, Proc. 38th International Symposium on Mathematical Foundations of Computer Science (MFCS'13), p. 266-277, 12 pp. 2013.
Publisher Springer
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
Impact factor Impact factor: 0.402 in 2005
RIV identification code RIV/00216224:14330/13:00072858
Organization unit Faculty of Informatics
ISBN 978-3-642-40312-5
ISSN 0302-9743
Doi http://dx.doi.org/10.1007/978-3-642-40313-2_25
UT WoS 000342994500025
Keywords in English multi-objective verification; stochastic games
Tags core_A, firank_A
Changed by Changed by: RNDr. Vojtěch Forejt, Ph.D., LL.B. (Hons), učo 99155. Changed: 11/4/2015 15:23.
Abstract
We study two-player stochastic games, where the goal of one player is to satisfy a formula given as a positive boolean combination of expected total reward objectives and the behaviour of the second player is adversarial. Such games are important for modelling, synthesis and verification of open systems with stochastic behaviour. We show that finding a winning strategy is PSPACE-hard in general and undecidable for deterministic strategies. We also prove that optimal strategies, if they exist, may require infinite memory and randomisation. However, when restricted to disjunctions of objectives only, memoryless deterministic strategies suffice, and the problem of deciding whether a winning strategy exists is NP-complete. We also present algorithms to approximate the Pareto sets of achievable objectives for the class of stopping games.
Links
LG13010, research and development projectName: Zastoupení ČR v European Research Consortium for Informatics and Mathematics (Acronym: ERCIM-CZ)
Investor: Ministry of Education, Youth and Sports of the CR
MUNI/33/IP1/2013, interní kód MUName: Podpora perspektivních výzkumných týmů Fakulty informatiky a vynikajících vědeckých pracovníků z jiných institucí působících na Fakultě informatiky (Acronym: PVT-VVPZ)
Investor: Masaryk University
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