Overview
Evolutionary computation includes Genetic Algorithms, Evolutionary Programming, Evolution Strategies, and Genetic Programming. In general any population based, selectionist algorithm that performs optimization or supports modeling is a form of evolutionary computation. This text covers primarily genetic algorithms and genetic programming as well as variations based on student projects and the author's research. It substantially reflects engineering (problem solving) rather than mathematical (theorem proving) methods. This book should appeal to undergraduates and beginning graduates in mathematics, computer science, engineering and biology.
Full Product Details
Author: Daniel Ashlock
Publisher: Springer-Verlag New York Inc.
Imprint: Springer-Verlag New York Inc.
Edition: 2006 ed.
Volume: PREL 200
Dimensions:
Width: 15.60cm
, Height: 3.30cm
, Length: 23.50cm
Weight: 2.220kg
ISBN: 9780387221960
ISBN 10: 0387221964
Pages: 572
Publication Date: 15 December 2005
Audience:
College/higher education
,
Undergraduate
,
Postgraduate, Research & Scholarly
Format: Hardback
Publisher's Status: Active
Availability: In Print
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Reviews
From the reviews: Evolutionary computation is a rich and diverse field ! . This book ! delivers a very practical introduction to the basics of the field ! . The tasks considered are all very motivational and advance from instructional toy examples to real world applications. ! The particular strength of the book lies in its didactic capabilities. The instructor will find different suggestions for selecting chapters leading to courses with different focus. ! This makes designing courses with the help of this book ! an easy task. (Thomas Jansen, Mathematical Reviews, Issue 2006 k) This book is based on the author's lecture notes of this lectures given at Iowa State University and is an introduction to evolurionary computation, a field which includes genetic algorithms, evolutionary programming, evolution strategies, and genetic programming. The text is intended for computer science, engineering, and other applied mathematics students. ! Finally, the book is a useful guide to using evolutionary algorithms as a problem solving tool. (Emil Ivanov, Zentralblatt MATH, Vol. 1102 (4), 2007) The present book is mainly focused on genetic algorithms and genetic programming, and successfully explains evolutionary computation through many different applications of these algorithms. ! I enjoyed reading this book ! . All of the chapters of the book are very well written, easy to understand ! . The book could provide a useful background to both undergraduate and graduate students commencing research studies in evolutionary computation. ! very useful for researchers who are planning to develop and apply evolutionary algorithms for their specific problems. (Adil Baykasoglu, The Computer Journal, Vol. 51 (6), 2008)
