Gödel–Dummett linear temporal logic

IF 5.1 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Juan Pablo Aguilera , Martín Diéguez , David Fernández-Duque , Brett McLean
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引用次数: 0

Abstract

We investigate a version of linear temporal logic whose propositional fragment is Gödel–Dummett logic (which is well known both as a superintuitionistic logic and a t-norm fuzzy logic). We define the logic using two natural semantics: first a real-valued semantics, where statements have a degree of truth in the real unit interval, and second a ‘bi-relational’ semantics. We then show that these two semantics indeed define one and the same logic: the statements that are valid for the real-valued semantics are the same as those that are valid for the bi-relational semantics. This Gödel temporal logic does not have any form of the finite model property for these two semantics: there are non-valid statements that can only be falsified on an infinite model. However, by using the technical notion of a quasimodel, we show that every falsifiable statement is falsifiable on a finite quasimodel, yielding an algorithm for deciding if a statement is valid or not. Later, we strengthen this decidability result by giving an algorithm that uses only a polynomial amount of memory, proving that Gödel temporal logic is PSPACE-complete. We also provide a deductive calculus for Gödel temporal logic, and show this calculus to be sound and complete for the above-mentioned semantics, so that all (and only) the valid statements can be proved with this calculus.
哥德尔-杜密特线性时态逻辑
我们研究了线性时间逻辑的一个版本,其命题片段是哥德尔-杜梅特逻辑(作为超直觉逻辑和 t 规范模糊逻辑而闻名)。我们使用两种自然语义来定义该逻辑:第一种是实值语义,其中语句在实数单位区间内具有真度;第二种是 "双关系 "语义。然后,我们证明这两种语义确实定义了同一个逻辑:实值语义中有效的语句与双关系语义中有效的语句是一样的。对于这两种语义,哥德尔时间逻辑不具有任何形式的有限模型属性:有一些非有效语句只能在无限模型上被证伪。然而,通过使用准模型的技术概念,我们证明了每个可证伪语句在有限准模型上都是可证伪的,从而得出了一种判定语句是否有效的算法。随后,我们通过给出一种只使用多项式内存的算法来加强这一可证实性结果,从而证明哥德尔时间逻辑是 PSPACE-完备的。我们还为哥德尔时间逻辑提供了一个演绎微积分,并证明这个微积分对于上述语义是健全和完备的,因此所有(且仅有)有效语句都可以用这个微积分证明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Artificial Intelligence
Artificial Intelligence 工程技术-计算机:人工智能
CiteScore
11.20
自引率
1.40%
发文量
118
审稿时长
8 months
期刊介绍: The Journal of Artificial Intelligence (AIJ) welcomes papers covering a broad spectrum of AI topics, including cognition, automated reasoning, computer vision, machine learning, and more. Papers should demonstrate advancements in AI and propose innovative approaches to AI problems. Additionally, the journal accepts papers describing AI applications, focusing on how new methods enhance performance rather than reiterating conventional approaches. In addition to regular papers, AIJ also accepts Research Notes, Research Field Reviews, Position Papers, Book Reviews, and summary papers on AI challenges and competitions.
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