高阶有效规划的定量行为推理:应用距离

Francesco Gavazzo
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引用次数: 41

摘要

本文研究了在模糊的推广背景下对Abramsky的应用相似度和双相似度的定量改进,模糊是一种具有线性类型系统的值调用λ-微积分,它可以表达程序的敏感性,丰富了代数运算,如Plotkin和Power。为了做到这一点,根据Lawvere对广义度量空间的分析,引入了一个一般的、抽象的框架来研究取量值的行为关系。将Barr的相对论(或松弛推广)概念推广到量子值关系中,适应和推广了一元拓扑领域的结果。然后定义了量子值有效应用相似性和双相似性的抽象概念,并分别在温和条件下证明了它们是相容的广义度量(在Lawvere的意义上)和伪度量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantitative Behavioural Reasoning for Higher-order Effectful Programs: Applicative Distances
This paper studies quantitative refinements of Abramsky's applicative similarity and bisimilarity in the context of a generalisation of Fuzz, a call-by-value λ-calculus with a linear type system that can express program sensitivity, enriched with algebraic operations à la Plotkin and Power. To do so a general, abstract framework for studying behavioural relations taking values over quantales is introduced according to Lawvere's analysis of generalised metric spaces. Barr's notion of relator (or lax extension) is then extended to quantale-valued relations, adapting and extending results from the field of monoidal topology. Abstract notions of quantale-valued effectful applicative similarity and bisimilarity are then defined and proved to be a compatible generalised metric (in the sense of Lawvere) and pseudometric, respectively, under mild conditions.
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