arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2011.14303cs.LO
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概率高阶不动点逻辑

A Probabilistic Higher-order Fixpoint Logic

Yo Mitani, Naoki Kobayashi, Takeshi Tsukada

AI总结:

本文提出概率高阶不动点逻辑PHFL,证明其表达力强于$\mu^p$-演算,有限马尔可夫链模型检验不可判定,并给出可判定片段。

摘要:

我们引入PHFL,即高阶不动点逻辑的概率扩展,它也可以被视为概率时态逻辑(如PCTL和$\mu^p$-演算)的高阶扩展。我们证明PHFL严格比$\mu^p$-演算更具表达力,并且有限马尔可夫链的PHFL模型检验问题即使对于PHFL的仅含$\mu$的一阶片段也是不可判定的。此外,完整的PHFL表达力远不止于此:我们给出了从Lubarsky的$\mu$-算术到PHFL的翻译,这意味着PHFL模型检验是$\Pi^1_1$-难和$\Sigma^1_1$-难的。作为正面结果,我们使用一种新颖的类型系统刻画了PHFL模型检验问题的一个可判定片段。

英文摘要:

We introduce PHFL, a probabilistic extension of higher-order fixpoint logic, which can also be regarded as a higher-order extension of probabilistic temporal logics such as PCTL and the $μ^p$-calculus. We show that PHFL is strictly more expressive than the $μ^p$-calculus, and that the PHFL model-checking problem for finite Markov chains is undecidable even for the $μ$-only, order-1 fragment of PHFL. Furthermore the full PHFL is far more expressive: we give a translation from Lubarsky's $μ$-arithmetic to PHFL, which implies that PHFL model checking is $Π^1_1$-hard and $Σ^1_1$-hard. As a positive result, we characterize a decidable fragment of the PHFL model-checking problems using a novel type system.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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