Detailed Information on Publication Record
2013
On Stochastic Games with Multiple Objectives
CHEN, Taolue, Vojtěch FOREJT, Marta KWIATKOWSKA, Aistis SIMAITIS, Clemens WILTSCHE et. al.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
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
Germany
Confidentiality degree
není předmětem státního či obchodního tajemství
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
UT WoS
000342994500025
Keywords in English
multi-objective verification; stochastic games
Změněno: 11/4/2015 15:23, RNDr. Vojtěch Forejt, Ph.D., LL.B. (Hons)
Abstract
V originále
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 project |
| ||
MUNI/33/IP1/2013, interní kód MU |
|