Introduction to Evolutionary Computing

A. E. Eiben

ISBN 10: 3662499851 / ISBN 13: 9783662499856

Verlag: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, 2016

Series: Natural Computing Series. Num Pages: 287 pages, 55 black & white illustrations, 12 colour illustrations, biography. BIC Classification: PBU; TJFM1; UYQ. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 16. Weight in Grams: 468. . 2016. Softcover reprint of the original 2nd ed. 2015. Paperback. . . . . Books ship from the US and Ireland. Bestandsnummer des Verkäufers V9783662499856

Inhaltsangabe:

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.

Über die Autorin bzw. den Autor:

Prof. Gusz Eiben received his Ph.D. in Computer Science in 1991. He was among the pioneers of evolutionary computing research in Europe, and served in key roles in steering committees, program committees and editorial boards for all the major related events and publications. His main research areas focused on multiparent recombination, constraint satisfaction, and self-calibrating evolutionary algorithms; he is now researching broader aspects of embodied intelligence and evolutionary robotics.

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.

Bibliografische Details

Titel: Introduction to Evolutionary Computing
Verlag: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Erscheinungsdatum: 2016
Einband: Softcover
Zustand: New