Introduction to Evolutionary Computing / Natural Computing Series (PDF)
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The overall structure of this new edition is three-tier: Part I presents the basics, Part II is concerned with methodological issues, and Part III discusses advanced topics. In the second edition the authors have reorganized the material to focus on problems, how to represent them, and then how to choose and design algorithms for different representations. They also added a chapter on problems, reflecting the overall book focus on problem-solvers, a chapter on parameter tuning, which they combined with the parameter control and "how-to" chapters into a methodological part, and finally a chapter on evolutionary robotics with an outlook on possible exciting developments in this field.
The book is suitable for undergraduate and graduate courses in artificial intelligence and computational intelligence, and for self-study by practitioners and researchers engaged with all aspects of bioinspired design and optimization.
Prof. James E. Smith received his Ph.D. in Computer Science in 1998. He is an associate professor of Interactive Artificial Intelligence and Head of the Artificial Intelligence Research Group in the Dept. of Computer Science and Creative Technologies of The University of the West of England, Bristol. His work has combined theoretical modelling with empirical studies in a number of areas, especially concerning self-adaptive and hybrid systems that "learn how to learn". His current research interests include optimization; machine learning and classification; memetic algorithms; statistical disclosure control; VLSI design verification; adaptive image segmentation and classification and computer vision systems for production quality control; and bioinformatics problems such as protein structure prediction and protein structure comparison.
- Autoren: A. E. Eiben , J. E. Smith
- 2015, 2nd ed. 2015, 287 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3662448742
- ISBN-13: 9783662448748
- Erscheinungsdatum: 01.07.2015
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- Größe: 3.88 MB
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“This second edition of the book under review is very timely and corresponds to Evolutionary Computation (EC)’s status as an established methodology. … The chapter subdivision into different algorithms used in the first edition … has been replaced by a more suitable student/researcher-oriented approach; this is also supported by the website www.evolutionarycomputation.org, which contains a trove of exercises, slides and extra bibliographic references.” (Anna I. Esparcia-Alcázar, Mathematical Reviews, May, 2016)
“Introduction to Evolutionary Computing is an excellent and readable text that should find a place on the bookshelf of anyone who researches and/or teaches in this domain. Suitable for a graduate course or upper-level undergraduate course in Evolutionary Computing, it is also a superior and well-organized reference book. … papers and presentations cited in the text provide a marvelous literature review. … The clarity of exposition and detail are excellent … .” (Jeffrey L. Popyack, Genetic Programming and Evolvable Machines, Vol. 17 (2), 2016)
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