{"title":"Toward rough set based insightful reasoning in intelligent systems","authors":"Andrzej Skowron , Jaroslaw Stepaniuk","doi":"10.1016/j.ins.2025.122078","DOIUrl":null,"url":null,"abstract":"<div><div>This paper explores a rough set-based approach for supporting insightful reasoning in Intelligent Systems (ISs). The novelty lies in the introduction of a new concept for approximate reasoning processes based on granular computations. Although many rough set theory extensions developed over time focus on reasoning about (partial) set inclusion, these approximation spaces sometimes fall short when dealing with crucial aspects of approximate reasoning within ISs. Specifically, these systems aim to construct high-quality approximations of compound decision granules that represent solutions. Here, we present the basis for insightful reasoning realized through approximate reasoning processes grounded in granular computations. By doing so, we provide a sufficiently rich basis for designing IS problem solvers. This basis allows ISs to restructure or adapt their reasoning based on the generated granular computations, ultimately leading to high-quality granular solutions.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"709 ","pages":"Article 122078"},"PeriodicalIF":8.1000,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Sciences","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0020025525002105","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This paper explores a rough set-based approach for supporting insightful reasoning in Intelligent Systems (ISs). The novelty lies in the introduction of a new concept for approximate reasoning processes based on granular computations. Although many rough set theory extensions developed over time focus on reasoning about (partial) set inclusion, these approximation spaces sometimes fall short when dealing with crucial aspects of approximate reasoning within ISs. Specifically, these systems aim to construct high-quality approximations of compound decision granules that represent solutions. Here, we present the basis for insightful reasoning realized through approximate reasoning processes grounded in granular computations. By doing so, we provide a sufficiently rich basis for designing IS problem solvers. This basis allows ISs to restructure or adapt their reasoning based on the generated granular computations, ultimately leading to high-quality granular solutions.
期刊介绍:
Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions.
Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.