马尔可夫链上双相似距离的完整定量演绎系统
A Complete Quantitative Deduction System for the Bisimilarity Distance on Markov Chains
AI总结:
本文为有限标记马尔可夫链上的双相似距离提出完全公理化,扩展了定量等式逻辑,并用于度量化的Kleene表示定理。
摘要:
本文针对有限标记马尔可夫链类别,提出了Desharnais等人定义的双相似距离的完全公理化。我们的公理化采用Mardare、Panangaden和Plotkin(LICS 2016)最近提出的等式逻辑的定量扩展风格,该逻辑使用以有理数索引的等式关系$t \equiv_\varepsilon s$,表达“$t$与$s$在误差$\varepsilon$内近似相等”。值得注意的是,我们的定量演绎系统通过引入一个处理概率分布之间Kantorovich距离的公理,以自然方式扩展了Stark和Smolka给出的概率双相似等式系统。该公理化随后被用于提出有限标记马尔可夫链的Kleene风格表示定理的度量扩展,该定理由Silva等人(Inf. Comput. 2011)以更一般的余代数方式提出。
英文摘要:
In this paper we propose a complete axiomatization of the bisimilarity distance of Desharnais et al. for the class of finite labelled Markov chains. Our axiomatization is given in the style of a quantitative extension of equational logic recently proposed by Mardare, Panangaden, and Plotkin (LICS 2016) that uses equality relations $t \equiv_\varepsilon s$ indexed by rationals, expressing that `$t$ is approximately equal to $s$ up to an error $\varepsilon$'. Notably, our quantitative deduction system extends in a natural way the equational system for probabilistic bisimilarity given by Stark and Smolka by introducing an axiom for dealing with the Kantorovich distance between probability distributions. The axiomatization is then used to propose a metric extension of a Kleene's style representation theorem for finite labelled Markov chains, that was proposed (in a more general coalgebraic fashion) by Silva et al. (Inf. Comput. 2011).
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