Genetic Programming Theory and Practice (Genetic Programming)

Features

• Cover Type: Hard Cover with 336 pages
• Published by: Springer
• Edition: 1st Edition November 30, 2003
• Written in: English
• ISBN 10 Number: 1402075812
• ISBN 13 Number: 978-1402075810
• Book Dimensions: 9 x 7.1 x 1 inches
• Weighs: 1.5 pounds

Product Review


From the reviews:

"This book contains 19 chapters that are based on respective research papers presented at the workshop ‘Genetic Program, Theory and Practice’. … The balanced combination of theoretical issues and application issues, along with the many new and interesting results described by the contributors make this book a useful source of up-to-date information on GP. The book will no doubt inspire new and old researchers and practitioners to push further the frontiers of GP theory and practice for the benefit of the international society." (Spyros Tzafestas, Journal of Intelligent and Robotic Systems, Vol. 45, 2006)

Product Description
Genetic Programming Theory and Practice explores the emerging interaction between theory and practice in the cutting-edge, machine learning method of Genetic Programming (GP). The material contained in this contributed volume was developed from a workshop at the University of Michigan's Center for the Study of Complex Systems where an international group of genetic programming theorists and practitioners met to examine how GP theory informs practice and how GP practice impacts GP theory. The contributions cover the full spectrum of this relationship and are written by leading GP theorists from major universities, as well as active practitioners from leading industries and businesses. Chapters include such topics as John Koza's development of human-competitive electronic circuit designs; David Goldberg's application of "competent GA" methodology to GP; Jason Daida's discovery of a new set of factors underlying the dynamics of GP starting from applied research; and Stephen Freeland's essay on the lessons of biology for GP and the potential impact of GP on evolutionary theory.
The book also includes chapters on the dynamics of GP, the selection of operators and population sizing, specific applications such as stock selection in emerging markets, predicting oil field production, modeling chemical production processes, and developing new diagnostics from genomic data.
Genetic Programming Theory and Practice is an great reference for researchers working in evolutionary algorithms and for practitioners seeking innovative methods to solve difficult computing problems.