Genetic and Evolutionary Computation

By: Rick Riolo (Editor), Terence Soule (Editor), Bill Worzel (Editor)

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Hardcover | 14 March 2007

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358 Pages

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23.39 x 15.6 x 2.06

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Genetic Programming Theory and Practice IV was developed from the fourth workshop at the University of Michigan's Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming (GP). Contributions from the foremost international researchers and practitioners in the GP arena examine the similarities and differences between theoretical and empirical results on real-world problems. The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application.

This volume represents a watershed moment in the GP field in that GP has begun to move from hand-crafted software used primarily in academic research, to an engineering methodology applied to commercial applications. It is a unique and indispensable tool for academics, researchers and industry professionals involved in GP, evolutionary computation, machine learning and artificial intelligence.

Industry Reviews

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"Every cutting-edge researcher, in every computational discipline, working on any real-world application, should make it a point to keep abreast of the ongoing progress of genetic programming theory and practice, which is currently available in this book. ... a great win-win synergy opportunity here for less-cutting-edge researchers to try these maturing tools on more intuitive data masses; they should be more able to appreciate the results, and the genetic programming cryptography community might then learn something new about how to interpret post-scientific results." (Chaim Scheff, ACM Computing Reviews, Vol. 49 (8), August, 2008)

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Non-Fiction Science Biology, Life Sciences Life Sciences in General Genetics excluding Medical Computing & I.T.Computer Science Artificial Intelligence Machine Learning Computer Programming & Software Development Algorithms & Data Structures Software Engineering

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Published: 7th July 2018

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Published: 30th January 2019

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Genetic programming : theory and practice	p. 1
Genome-wide genetic analysis using genetic programming	p. 11
Lifting the curse of dimensionality	p. 29
GP for classifying cancer data and controlling humanoid robots	p. 41
Boosting improves stability and accuracy of genetic programming in biological sequence classification	p. 61
Orthogonal evolution of teams : a class of algorithms for evolving teams with inversely correlated errors	p. 79
Multidimensional tags, cooperative populations, and genetic programming	p. 97
Coevolving fitness models for accelerating evolution and reducing evaluations	p. 113
Multi-domain observations concerning the use of genetic programming to automatically synthesize human-competitive designs for analog circuits, optical lens systems, controllers, antennas, mechanical systems, and quantum computing circuits	p. 131
Robust Pareto front genetic programming parameter selection based on design of experiments and industrial data	p. 149
Pursuing the Pareto paradigm : tournaments, algorithm variations and ordinal optimization	p. 167
Applying genetic programming to reservoir history matching problem	p. 187
Comparison of robustness of three filter design strategies using genetic programming and bond graphs	p. 203
Design of posynomial models for mosfets : symbolic regression using genetic algorithms	p. 219
Phase transitions in genetic programming search	p. 237
Efficient Markov chain model of machine code program execution and halting	p. 257
A re-examination of a real world blood flow modeling problem using context-aware crossover	p. 279
Large-scale, time-constrained symbolic regression	p. 299
Stock selection : an innovative application of genetic programming methodology	p. 315
Table of Contents provided by Blackwell. All Rights Reserved.

Genetic and Evolutionary Computation

At a Glance

Hardcover

Industry Reviews

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How to return your order

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You Can Find This Book In

Other Editions and Formats

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