Computational Intelligence

A Methodological Introduction

Rudolf Kruse, Sanaz Mostaghim, Christian Borgelt, Christian Braune, Matthias Steinbrecher (Autoren)

Buch | Hardcover

XIV, 639 Seiten

2022 | 3rd ed. 2022
Springer International Publishing (Verlag)
978-3-030-42226-4 (ISBN)

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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.

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, Dr. Andreas Nürnberger is a full Professor of Data and Knowledge Engineering, and Dr. Christian Braune a Research Assistant 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.

Introduction.- Part I: Neural Networks.- Introduction.- Threshold Logic Units.- General Neural Networks.- Multi-Layer Perceptrons.- Radial Basis Function Networks.- Self-Organizing Maps.- Hopfield Networks.- Recurrent Networks.- Mathematical Remarks for Neural Networks.- Part II: Evolutionary Algorithms.- Introduction to Evolutionary Algorithms.- Elements of Evolutionary Algorithms.- Fundamental Evolutionary Algorithms.- Computational Swarm Intelligence.- Part III: Fuzzy Systems.- Fuzzy Sets and Fuzzy Logic.- The Extension Principle.- Fuzzy Relations.- Similarity Relations.- Fuzzy Control.- Fuzzy Data Analysis.- Part IV: Bayes and Markov Networks.- Introduction to Bayes Networks.- Elements of Probability and Graph Theory.- Decompositions.- Evidence Propagation.- Learning Graphical Models.- Belief Revision.- Decision Graphs.

"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)

Erscheinungsdatum	30.03.2022
Reihe/Serie	Texts in Computer Science
Zusatzinfo	XIV, 639 p. 324 illus., 42 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	1142 g
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
Themenwelt	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
Schlagworte	Artificial Neural Networks • Bayesian networks • Computational Intelligence • evolutionary algorithms • Fuzzy Systems
ISBN-10	3-030-42226-7 / 3030422267
ISBN-13	978-3-030-42226-4 / 9783030422264
Zustand	Neuware