Genetic Programming Theory and Practice VI

by Rick Riolo (Editor), Terence Soule (Editor), Bill Worzel (Editor)

Overview

Genetic Programming Theory and Practice VI was developed from the sixth 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.

These contributions address several significant interdependent themes which emerged from this year’s workshop, including: (1) Making efficient and effective use of test data. (2) Sustaining the long-term evolvability of our GP systems. (3) Exploiting discovered subsolutions for reuse. (4) Increasing the role of a Domain Expert.

Product Details

ISBN-13:	9780387876221
Publisher:	Springer US
Publication date:	12/02/2008
Series:	Genetic and Evolutionary Computation
Edition description:	2009
Pages:	274
Product dimensions:	6.30(w) x 9.30(h) x 0.70(d)

Table of Contents

Genetic Programming: Theory and Practice.- APopulationBased Study ofEvolutionaryDynamics inGeneticProgramming.- An Application of Information Theoretic Selection to Evolution of Models with Continuous-valued Inputs.- Pareto Cooperative-Competitive Genetic Programming: A Classification Benchmarking Study.- Genetic Programming with Historically Assessed Hardness.- Crossover and Sampling Biases on Nearly Uniform Landscapes.- Analysis of theEffects ofElitismonBloat inLinear and Tree-basedGenetic Programming.- Automated Extraction of Expert Domain Knowledge from Genetic Programming Synthesis Results.- Does Complexity Matter? Artificial Evolution, Computational Evolution and the Genetic Analysis of Epistasis in Common Human Diseases..- Exploiting Trustable Models via Pareto GP for Targeted Data Collection.- Evolving Effective Incremental Solvers for SAT with a Hyper-Heuristic Framework Based on Genetic Programming.- ConstrainedGenetic Programming toMinimizeOverfitting in SkSelection.- Co-Evolving Trading Strategies toAnalyzeBoundedRationality inDouble Auction Markets..- Profiling Symbolic Regression-Classification.- Accelerating Genetic Programming through Graphics Processing Units..- Genetic Programming for Incentive-Based Design within a Cultural Algorithms Framework..

Editorial Reviews

From the reviews:

"This book is a collection of contributions from various theorists and practitioners working in the genetic programming (GP) field. … anyone who is interested in the subject should monitor the ongoing research; this volume is an essential assistant for the task. … I found the book interesting … that stimulate the researcher to think of further applications of the presented techniques and methodologies. … I recommend it not only to GP researchers and practitioners, but also to any scientist dealing with optimization problems … ." (Lefteris Angelis, ACM Computing Reviews, March, 2009)

From the Publisher