Metric quantifiers and counting in timed logics and automata

IF 0.8 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS Information and Computation Pub Date : 2025-01-17 DOI:10.1016/j.ic.2025.105268
Hsi-Ming Ho , Khushraj Madnani
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引用次数: 0

Abstract

We study the expressiveness of the pointwise interpretations (i.e. over timed words) of some predicate and temporal logics with metric and counting features. We show that counting in the unit interval (0,1) is strictly weaker than counting in (0,b) with arbitrary b0; moreover, allowing the latter to be included in temporal logics leads to expressive completeness for the metric predicate logic Q2MLO, recovering the corresponding result for the continuous interpretations (i.e. over signals). Exploiting this connection, we show that in contrast to the continuous case, adding ‘punctual’ predicates into Q2MLO is still insufficient for the full expressive power of the Monadic First-Order Logic of Order and Metric (FO[<,+1]); as a remedy, we propose a generalisation of the recently proposed Pnueli automata modalities and show that the resulting metric temporal logic is expressively complete for FO[<,+1]. On the practical side, we propose a compositional construction from metric interval temporal logic with counting or similar extensions to timed automata, which is more amenable to implementation based on existing tools that support on-the-fly model checking.
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来源期刊
Information and Computation
Information and Computation 工程技术-计算机:理论方法
CiteScore
2.30
自引率
0.00%
发文量
119
审稿时长
140 days
期刊介绍: Information and Computation welcomes original papers in all areas of theoretical computer science and computational applications of information theory. Survey articles of exceptional quality will also be considered. Particularly welcome are papers contributing new results in active theoretical areas such as -Biological computation and computational biology- Computational complexity- Computer theorem-proving- Concurrency and distributed process theory- Cryptographic theory- Data base theory- Decision problems in logic- Design and analysis of algorithms- Discrete optimization and mathematical programming- Inductive inference and learning theory- Logic & constraint programming- Program verification & model checking- Probabilistic & Quantum computation- Semantics of programming languages- Symbolic computation, lambda calculus, and rewriting systems- Types and typechecking
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