Abstract
We introduce p-Automata, which are automata that accept languages of Markov chains, by adapting notions and techniques from alternating tree automata to the realm of Markov chains. The set of languages of p-automata is closed under Boolean operations, and for every PCTL formula it contains the language of the set of models of the formula. Furthermore, the language of every p-automaton is closed under probabilistic bisimulation. Similar to tree automata, whose acceptance is defined via two-player games, we define acceptance of Markov chains by p-automata through two-player stochastic games. We show that acceptance is solvable in EXPTIME; but for automata that arise from PCTL formulas acceptance matches that of PCTL model checking, namely, linear in the formula and polynomial in the Markov chain. We also derive a notion of simulation between p-automata that approximates language containment in EXPTIME and is complete for Markov chains. These foundations therefore enable abstraction-based probabilistic model checking for probabilistic specifications that subsume Markov chains, and LTL and CTL* like logics.
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