Produktbild
A. E. Eiben

Introduction to Evolutionary Computing

Buch

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 possib… Mehr

CHF 56.50

Preise inkl. MwSt. und Versandkosten (Portofrei ab CHF 40.00)

Versandfertig innerhalb 1-3 Werktagen

Produktdetails


Weitere Autoren: Smith, J. E.
  • ISBN: 978-3-662-49985-6
  • EAN: 9783662499856
  • Produktnummer: 21428101
  • Verlag: Springer Berlin Heidelberg
  • Sprache: Englisch
  • Erscheinungsjahr: 2016
  • Seitenangabe: 304 S.
  • Masse: H23.6 cm x B15.8 cm x D2.0 cm 475 g
  • Auflage: Softcover reprint of the original 2nd ed. 2015
  • Abbildungen: Paperback
  • Gewicht: 475

Über 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.

3 weitere Werke von A. E. Eiben:


Bewertungen


0 von 0 Bewertungen

Geben Sie eine Bewertung ab!

Teilen Sie Ihre Erfahrungen mit dem Produkt mit anderen Kunden.