Reasoning with Rough Sets [electronic resource] : Logical Approaches to Granularity-Based Framework / by Seiki Akama, Tetsuya Murai, Yasuo Kudo.
By: Akama, Seiki [author.]
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Contributor(s): Murai, Tetsuya [author.] | Kudo, Yasuo [author.] | SpringerLink (Online service).
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BookSeries: Intelligent Systems Reference Library: 142Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: X, 201 p. 12 illus., 7 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319726915.Subject(s): Computational intelligence | Artificial intelligence | Computational Intelligence | Artificial IntelligenceAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
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Springer Nature eBookSummary: This book explores reasoning with rough sets by developing a granularity-based framework. It begins with a brief description of rough set theory. Next, we examine some relations between rough set theory and non-classical logics including modal logic. We also develop a granularity-based framework for reasoning in which various types of reasoning can be formalized. This book will be of interest to researchers working on the areas in Artificial Intelligence, database and logic.
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This book explores reasoning with rough sets by developing a granularity-based framework. It begins with a brief description of rough set theory. Next, we examine some relations between rough set theory and non-classical logics including modal logic. We also develop a granularity-based framework for reasoning in which various types of reasoning can be formalized. This book will be of interest to researchers working on the areas in Artificial Intelligence, database and logic.
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