Computational Intelligence von Rudolf Kruse | A Methodological Introduction | ISBN 9781447172963

Computational Intelligence

A Methodological Introduction

von Rudolf Kruse, Christian Borgelt, Christian Braune, Sanaz Mostaghim und Matthias Steinbrecher
Mitwirkende
Autor / AutorinRudolf Kruse
Autor / AutorinChristian Borgelt
Autor / AutorinChristian Braune
Autor / AutorinSanaz Mostaghim
Autor / AutorinMatthias Steinbrecher
Beiträge vonFrank Klawonn
Beiträge vonChristian Moewes
Buchcover Computational Intelligence | Rudolf Kruse | EAN 9781447172963 | ISBN 1-4471-7296-5 | ISBN 978-1-4471-7296-3

“It is a great book, very well written, that presents solid content in a very rigorous theoretical and practical way and provides an excellent methodological guide to the area of computational intelligence —one that could be qualified as a ‘must’ for the library of any student, professor, researcher or professional in that area.” (José Luis Verdegay, Mathematical Reviews, May, 2017)

Computational Intelligence

A Methodological Introduction

von Rudolf Kruse, Christian Borgelt, Christian Braune, Sanaz Mostaghim und Matthias Steinbrecher
Mitwirkende
Autor / AutorinRudolf Kruse
Autor / AutorinChristian Borgelt
Autor / AutorinChristian Braune
Autor / AutorinSanaz Mostaghim
Autor / AutorinMatthias Steinbrecher
Beiträge vonFrank Klawonn
Beiträge vonChristian Moewes

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 second edition has been fully revised and expanded with new content on swarm intelligence, deep learning, fuzzy data analysis, and discrete decision graphs. 
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 colonyoptimization and probabilistic graphical models.