Overview
- Written by a team of highly-regarded experts, with extensive experience in both academia and industry
- Provides supplementary material on module descriptions, lecture slides, exercises with solutions, and software tools
- Addresses deep learning, scalarization, large-scale optimization algorithms, and collective decision-making algorithms
Part of the book series: Texts in Computer Science (TCS)
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About this book
This textbook provides a clear and logical introduction to the field, covering the fundamental concepts, algorithms and practical implementations behind efforts to develop systems that exhibit intelligent behavior in complex environments. This enhanced third edition has been fully revised and expanded with new content on deep learning, scalarization methods, large-scale optimization algorithms, and collective decision-making algorithms.
Features: provides supplementary material at an associated website; contains numerous classroom-tested examples and definitions throughout the text; presents useful insights into all that is necessary for the successful application of computational intelligence methods; explains the theoretical background underpinning proposed solutions to common problems; discusses in great detail the classical areas of artificial neural networks, fuzzy systems and evolutionary algorithms; reviews the latest developments in the field, covering such topics as ant colony optimization and probabilistic graphical models.
Features: provides supplementary material at an associated website; contains numerous classroom-tested examples and definitions throughout the text; presents useful insights into all that is necessary for the successful application of computational intelligence methods; explains the theoretical background underpinning proposed solutions to common problems; discusses in great detail the classical areas of artificial neural networks, fuzzy systems and evolutionary algorithms; reviews the latest developments in the field, covering such topics as ant colony optimization and probabilistic graphical models.
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Keywords
Table of contents (30 chapters)
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Front Matter
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Evolutionary Algorithms
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Front Matter
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Fuzzy Systems
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Front Matter
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Reviews
“The book presents a thorough exposition of the main concepts of computational intelligence. … It is an interesting book that may serve very well a wide audience, providing material for researchers, students as well as people working in industry.” (Catalin Stoean, zbMATH 1500.68001, 2023)
“The authors have written Computational intelligence in such a way that it can serve as both a textbook and a helpful reference book for students and practitioners of computing science and related fields. The presentation is careful and friendly yet technically sound.” (Soubhik Chakraborty, Computing Reviews, March 7, 2023)
Authors and Affiliations
About the authors
Dr. Rudolf Kruse is the former leader of the Computational Intelligence Research Group and now Emeritus Professor of the Department of Computer Science at the University of Magdeburg, Germany. Dr. Sanaz Mostaghim is a full Professor of Computer Science and Dr. Christian Braune is a Senior Lecturer at the same institution. Dr. Christian Borgelt is a Professor of Data Science at the Paris Lodron University of Salzburg, Austria. Dr. Matthias Steinbrecher is a Development Architect at SAP SE, Potsdam, Germany.
Bibliographic Information
Book Title: Computational Intelligence
Book Subtitle: A Methodological Introduction
Authors: Rudolf Kruse, Sanaz Mostaghim, Christian Borgelt, Christian Braune, Matthias Steinbrecher
Series Title: Texts in Computer Science
DOI: https://doi.org/10.1007/978-3-030-42227-1
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-42226-4Published: 29 March 2022
Softcover ISBN: 978-3-030-42229-5Published: 30 March 2023
eBook ISBN: 978-3-030-42227-1Published: 26 March 2022
Series ISSN: 1868-0941
Series E-ISSN: 1868-095X
Edition Number: 3
Number of Pages: XIV, 639
Number of Illustrations: 282 b/w illustrations, 42 illustrations in colour
Topics: Artificial Intelligence, Mathematical and Computational Engineering, Computational Intelligence, Theory of Computation