Markov Decision Processes with Sure Parity and Multiple Reachability Objectives

Raphaël Berthon, Joost-Pieter Katoen, Tobias Winkler
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Abstract

This paper considers the problem of finding strategies that satisfy a mixture of sure and threshold objectives in Markov decision processes. We focus on a single $\omega$-regular objective expressed as parity that must be surely met while satisfying $n$ reachability objectives towards sink states with some probability thresholds too. We consider three variants of the problem: (a) strict and (b) non-strict thresholds on all reachability objectives, and (c) maximizing the thresholds with respect to a lexicographic order. We show that (a) and (c) can be reduced to solving parity games, and (b) can be solved in $\sf{EXPTIME}$. Strategy complexities as well as algorithms are provided for all cases.
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具有确定奇偶性和多重可达性目标的马尔可夫决策过程
本文探讨了在马尔可夫决策过程中寻找满足确定目标和阈值目标混合的策略的问题。我们关注的是以奇偶性表示的单一 $\omega$ 规则目标,该目标必须在满足 $n$ 可到达性目标的同时,还必须满足一些概率阈值。我们考虑了该问题的三种变体:(a) 所有可达性目标上的严格阈值和 (b) 非严格阈值,以及 (c) 最大化相对于词典顺序的阈值。我们证明(a)和(c)可以简化为求解奇偶性博弈,而(b)可以在$\sf{EXPTIME}$内求解。我们提供了所有情况的策略复杂性和算法。
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