Fuzzy approaches for soft computing and approximate reasoning : theories and applications : dedicated to Bernadette Bouchon-Meunier
Author(s)
Bibliographic Information
Fuzzy approaches for soft computing and approximate reasoning : theories and applications : dedicated to Bernadette Bouchon-Meunier
（Studies in fuzziness and soft computing, v. 394）
Springer, c2021 [i.e. c2020]
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Includes bibliographical references
Description and Table of Contents
Description
This book gathers cutting-edge papers in the area of Computational Intelligence, presented by specialists, and covering all major trends in the research community in order to provide readers with a rich primer. It presents an overview of various soft computing topics and approximate reasoning-based approaches, both from theoretical and applied perspectives. Numerous topics are covered: fundamentals aspects of fuzzy sets theory, reasoning approaches (interpolative, analogical, similarity-based), decision and optimization theory, fuzzy databases, soft machine learning, summarization, interpretability and XAI. Moreover, several application-based papers are included, e.g. on image processing, semantic web and intelligent tutoring systems. This book is dedicated to Bernadette Bouchon-Meunier in honor of her achievements in Computational Intelligence, which, throughout her career, have included profuse and diverse collaborations, both thematically and geographically.
Table of Contents
Chapter 1: The Fuzzy Theoretic Turn.- Chapter 2: Membership functions.- Chapter 3: The evolution of the notion of overlap functions.- Chapter 4: Interpolative reasoning: valid, specificity-gradual.- Chapter 5: A similarity-based three-valued modal logic approach to reason with prototypes and counterexamples.- Chapter 6: Analogy.- Chapter 7: The role of the context in decision and optimization problems.- Chapter 8: Decision rules under vague and uncertain information.- Chapter 9: Abstract Models for Systems Identification.- Chapter 10: Fuzzy Systems Interpretability: What, Why and How.- Chapter 11: Fuzzy Clustering Models and Their Related Concepts.
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