Evolutionary design of intelligent systems in modeling, simulation and control /

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Bibliographic Details
Imprint:Berlin : Springer, ©2009.
Description:1 online resource (ix, [327] pages) : illustrations.
Language:English
Series:Studies in computational intelligence, 1860-949X ; v. 257
Studies in computational intelligence ; v. 257.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11073531
Hidden Bibliographic Details
Other authors / contributors:Castillo, Oscar, 1959-
Pedrycz, Witold, 1953-
Kacprzyk, Janusz.
ISBN:9783642045141
3642045146
9783642045134
3642045138
Notes:Includes bibliographical references and index.
Print version record.
Summary:The editors describe in this book, new methods for evolutionary design of intelligent systems using soft computing and their applications in modeling, simulation and control. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in four main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of evolutionary design of fuzzy systems in intelligent control, which consists of papers that propose new methods for designing and optimizing intelligent controllers for different applications. The second part contains papers with the main theme of evolutionary design of intelligent systems for pattern recognition applications, which are basically papers using evolutionary algorithms for optimizing modular neural networks with fuzzy systems for response integration, for achieving pattern recognition in different applications. The third part contains papers with the themes of models for learning and social simulation, which are papers that apply intelligent systems to the problems of designing learning objects and social agents. The fourth part contains papers that deal with intelligent systems in robotics applications and hardware implementations.
Other form:Print version: Evolutionary design of intelligent systems in modeling, simulation and control. Berlin : Springer, ©2009 9783642045134
Description
Summary:We describe in this book, new methods for evolutionary design of intelligent s- tems using soft computing and their applications in modeling, simulation and c- trol. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in four main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of evolutionary design of fuzzy systems in intelligent control, which consists of papers that propose new methods for designing and optimizing intelligent controllers for different applications. The second part c- tains papers with the main theme of evolutionary design of intelligent systems for pattern recognition applications, which are basically papers using evolutionary al- rithms for optimizing modular neural networks with fuzzy systems for response - tegration, for achieving pattern recognition in different applications. The third part contains papers with the themes of models for learning and social simulation, which are papers that apply intelligent systems to the problems of designing learning - jects and social agents. The fourth part contains papers that deal with intelligent s- tems in robotics applications and hardware implementations. In the part of Intelligent Control there are 5 papers that describe different c- tributions on evolutionary optimization of fuzzy systems in intelligent control. The first paper, by Ricardo Martinez-Marroquin et al.
Physical Description:1 online resource (ix, [327] pages) : illustrations.
Bibliography:Includes bibliographical references and index.
ISBN:9783642045141
3642045146
9783642045134
3642045138
ISSN:1860-949X
;