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On Omega-Languages Defined by Mean-Payoff Conditions

机译:关于均值支付条件定义的欧米茄语言

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In quantitative verification, system states/transitions have associated payoffs, and these are used to associate mean-payoffs with infinite behaviors. In this paper, we propose to define ω-languages via Boolean queries over mean-payoffs. Requirements concerning averages such as "the number of messages lost is negligible" are not ω-regular, but specifiable in our framework. We show that, for closure under intersection, one needs to consider multi-dimensional payoffs. We argue that the acceptance condition needs to examine the set of accumulation points of sequences of mean-payoffs of prefixes, and give a precise characterization of such sets. We propose the class of multi-threshold mean-payoff languages using acceptance conditions that are Boolean combinations of inequalities comparing the minimal or maximal accumulation point along some coordinate with a constant threshold. For this class of languages, we study expressiveness, closure properties, analyzability, and Borel complexity.
机译:在定量验证中,系统状态/转换具有关联的收益,并且这些收益/收益用于将均值收益与无限行为关联。在本文中,我们建议通过均值收益的布尔查询来定义ω语言。关于平均值的要求,例如“丢失的消息数量可以忽略不计”,不是ω-常规的,而是在我们的框架中可指定的。我们表明,对于相交下的封闭,需要考虑多维收益。我们认为,接受条件需要检查前缀的均值支付序列的累积点集,并给出此类集的精确特征。我们使用接受条件提出一类多阈值均值支付语言,该条件是不等式的布尔组合,将沿某个坐标的最小或最大累积点与恒定阈值进行比较。对于此类语言,我们研究表达性,闭包性,可分析性和Borel复杂性。

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