Optimal strategy synthesis in stochastic Müller games Conference Paper


Author(s): Chatterjee, Krishnendu
Title: Optimal strategy synthesis in stochastic Müller games
Title Series: LNCS
Affiliation
Abstract: The theory of graph games with ω-regular winning conditions is the foundation for modeling and synthesizing reactive processes. In the case of stochastic reactive processes, the corresponding stochastic graph games have three players, two of them (System and Environment) behaving adversarially, and the third (Uncertainty) behaving probabilistically. We consider two problems for stochastic graph games: the qualitative problem asks for the set of states from which a player can win with probability 1 (almost-sure winning); and the quantitative problem asks for the maximal probability of winning (optimal winning) from each state. We consider ω-regular winning conditions formalized as Müller winning conditions. We present optimal memory bounds for pure almost-sure winning and optimal winning strategies in stochastic graph games with Müller winning conditions. We also present improved memory bounds for randomized almost-sure winning and optimal strategies.
Conference Title: FoSSaCS: Foundations of Software Science and Computation Structures
Volume: 4423
Conference Dates: March 24 - April 1, 2007
Conference Location: Braga, Portugal
Publisher: Springer  
Date Published: 2007-07-02
Start Page: 138
End Page: 152
Sponsor: This research was supported in part by the the AFOSR MURI grant F49620-00-1- 0327, and the NSF grant CCR-0225610.
DOI: 10.1007/978-3-540-71389-0_11
Open access: no
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