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Reasoning with Rough Sets

Logical Approaches to Granularity-Based Framework

  • Book
  • © 2018

Overview

  • Explores reasoning with rough sets by developing a granularity-based framework
  • Includes a brief description of the rough set theory
  • Examines the relations between rough set theory and nonclassical logics including modal logic
  • Develops a granularity-based framework for reasoning in which various types of reasoning can be formalized
  • Includes supplementary material: sn.pub/extras

Part of the book series: Intelligent Systems Reference Library (ISRL, volume 142)

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Table of contents (6 chapters)

Keywords

About this book

This book explores reasoning with rough sets by developing a granularity-based framework. It begins with a brief description of the rough set theory, then examines selected relations between rough set theory and non-classical logics including modal logic. In addition, it develops a granularity-based framework for reasoning in which various types of reasoning can be formalized. The book will be of interest to all researchers whose work involves Artificial Intelligence, databases and/or logic.

Authors and Affiliations

  • Kawasaki-shi, Japan

    Seiki Akama

  • Chitose Institute of Science and Technology , Chitose, Japan

    Tetsuya Murai

  • Muroran Institute of Technology, Muroran, Japan

    Yasuo Kudo

Bibliographic Information

  • Book Title: Reasoning with Rough Sets

  • Book Subtitle: Logical Approaches to Granularity-Based Framework

  • Authors: Seiki Akama, Tetsuya Murai, Yasuo Kudo

  • Series Title: Intelligent Systems Reference Library

  • DOI: https://doi.org/10.1007/978-3-319-72691-5

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing AG 2018

  • Hardcover ISBN: 978-3-319-72690-8Published: 31 January 2018

  • Softcover ISBN: 978-3-319-89195-8Published: 06 June 2019

  • eBook ISBN: 978-3-319-72691-5Published: 30 December 2017

  • Series ISSN: 1868-4394

  • Series E-ISSN: 1868-4408

  • Edition Number: 1

  • Number of Pages: X, 201

  • Number of Illustrations: 5 b/w illustrations, 7 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

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