Publication details

Approximating Values of Generalized-Reachability Stochastic Games

Authors

ASHOK Pranav CHATTERJEE Krishnendu KŘETÍNSKÝ Jan WEININGER Maximilian WINKLER Tobias

Year of publication 2020
Type Article in Proceedings
Conference LICS '20: 35th Annual ACM/IEEE Symposium on Logic in Computer Science, Saarbrücken, Germany, July 8-11, 2020.
MU Faculty or unit

Faculty of Informatics

Citation
Doi https://doi.org/10.1145/3373718.3394761
Description Simple stochastic games are turn-based 2-player games with a reachability objective. The basic question asks whether one player can ensure reaching a given target with at least a given probability. A natural extension is games with a conjunction of such conditions as objective. Despite a plethora of recent results on the analysis of systems with multiple objectives, the decidability of this basic problem remains open. In this paper, we present an algorithm approximating the Pareto frontier of the achievable values to a given precision. Moreover, it is an anytime algorithm, meaning it can be stopped at any time returning the current approximation and its error bound.

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