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Controller Synthesis and Verification for Markov Decision Processes with Qualitative Branching Time Objectives

机译:具有定性分支时间目标的马尔可夫决策过程的控制器综合与验证

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We show that the controller synthesis and verification problems for Markov decision processes with qualitative PECTL{sup}* objectives are 2-EXPTIME complete. More precisely, the algorithms are polynomial in the size of a given Markov decision process and doubly exponential in the size of a given qualitative PECTL{sup}* formula. Moreover, we show that if a given qualitative PECTL{sup}* objective is achievable by some strategy, then it is also achievable by an effectively constructible one-counter strategy, where the associated complexity bounds are essentially the same as above. For the fragment of qualitative PCTL objectives, we obtain EXPTIME completeness and the algorithms are only singly exponential in the size of the formula.
机译:我们表明,具有定性Pectl {sup} *目标的马尔可夫决策过程的控制器综合和验证问题是2-exptime完成。更确切地说,算法是在给定的马尔可夫决策过程的大小的多项式,并且在给定的定性pect1 {sup} *公式的大小中的双重指数。此外,如果通过一些策略可以实现给定的定性pectl {sup} *目标,则还可以通过有效结构的单反策略来实现,其中相关的复杂性界限基本相同。对于定性PCTL目标的片段,我们获得了EXPTIME完整性,并且算法仅在公式的大小上单独指数。

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