Generalized possibility computation tree logic with frequency and its model checking

IF 3.2 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Approximate Reasoning Pub Date : 2024-07-15 DOI:10.1016/j.ijar.2024.109249
Qing He , Wuniu Liu , Yongming Li
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Abstract

In recent years, there has been significant research in the field of possibilistic temporal logic. However, existing works have not yet addressed the issue of frequency, which is a common form of uncertainty in the real world. This article aims to fill this gap by incorporating frequency information into possibilistic temporal logic and focusing on the model-checking problem of generalized possibility computation tree logic (GPoCTL) with frequency information. Specifically, we introduce generalized possibility computation tree logic with frequency (GPoCTLF). Although its syntax can be considered as an extension of frequency constraints of the always operator (□) in GPoCTL, they are fundamentally different in semantics and model-checking methods. To facilitate this extension, useful frequency words such as “always”, “usually”, “often”, “sometimes”, “occasionally”, “rarely”, “hardly ever” and “never” are defined as fuzzy frequency operators in this article. Therefore, this article focuses on investigating the model-checking problem of the frequency-constrained always operator. In addition, we analyze the relationship between some GPoCTLF path formulas and GPoCTL path formulas. Then, we provide a model-checking algorithm for GPoCTLF and analyze its time complexity. Finally, an example of a social network is used to illustrate the calculation process of the proposed method and its potential applications.

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带频率的广义可能性计算树逻辑及其模型检查
近年来,在可能性时态逻辑领域开展了大量研究。然而,现有研究尚未涉及频率问题,而频率是现实世界中常见的不确定性形式。本文旨在填补这一空白,将频率信息纳入可能性时态逻辑,并重点研究具有频率信息的广义可能性计算树逻辑(GPoCTL)的模型检验问题。具体来说,我们引入了带频率的广义可能性计算树逻辑(GPoCTLF)。虽然它的语法可以看作是 GPoCTL 中始终算子(□)的频率约束的扩展,但它们在语义和模型检查方法上有着本质的区别。为了便于扩展,本文将 "总是"、"通常"、"经常"、"有时"、"偶尔"、"很少"、"几乎没有 "和 "从不 "等有用的频率词定义为模糊频率算子。因此,本文重点研究频率受限总是算子的模型检验问题。此外,我们还分析了一些 GPoCTLF 路径公式与 GPoCTL 路径公式之间的关系。然后,我们提供了 GPoCTLF 的模型检查算法,并分析了其时间复杂性。最后,我们以一个社交网络为例,说明了所提方法的计算过程及其潜在应用。
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来源期刊
International Journal of Approximate Reasoning
International Journal of Approximate Reasoning 工程技术-计算机:人工智能
CiteScore
6.90
自引率
12.80%
发文量
170
审稿时长
67 days
期刊介绍: The International Journal of Approximate Reasoning is intended to serve as a forum for the treatment of imprecision and uncertainty in Artificial and Computational Intelligence, covering both the foundations of uncertainty theories, and the design of intelligent systems for scientific and engineering applications. It publishes high-quality research papers describing theoretical developments or innovative applications, as well as review articles on topics of general interest. Relevant topics include, but are not limited to, probabilistic reasoning and Bayesian networks, imprecise probabilities, random sets, belief functions (Dempster-Shafer theory), possibility theory, fuzzy sets, rough sets, decision theory, non-additive measures and integrals, qualitative reasoning about uncertainty, comparative probability orderings, game-theoretic probability, default reasoning, nonstandard logics, argumentation systems, inconsistency tolerant reasoning, elicitation techniques, philosophical foundations and psychological models of uncertain reasoning. Domains of application for uncertain reasoning systems include risk analysis and assessment, information retrieval and database design, information fusion, machine learning, data and web mining, computer vision, image and signal processing, intelligent data analysis, statistics, multi-agent systems, etc.
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