Reasoning with Rough Sets [electronic resource] : Logical Approaches to Granularity-Based Framework /
By: Akama, Seiki [author.].
Contributor(s): Murai, Tetsuya [author.] | Kudo, Yasuo [author.] | SpringerLink (Online service).
Series: 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. | Binding - Card Paper |.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319726915.Subject(s): Computer Engineering
| Computational Intelligence | Artificial IntelligenceDDC classification: 006.3 Online resources: Click here to access eBook in Springer Nature platform. (Within Campus only.)
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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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