Modal Stochastic Games
نویسنده
چکیده
This paper presents an abstraction-refinement framework for Segala’s probabilistic automata (PA), a slight variant of Markov decision processes. We use Condon and Ladner’s two-player probabilistic game automata extended with possible and required transitions — as in Larsen and Thomsen’s modal transition systems — as abstract models. The key idea is to refine player-one and player-two states separately resulting in a nested abstract-refine loop. We show the adequacy of this approach for obtaining tight bounds on extremal reachability probabilities.
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