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Genetic Programming Theory and Practice VI

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

02.12.2008

Abbildungen

XIV, 274 p. 100 illus.

Herausgeber

Rick Riolo + weitere

Verlag

Springer Us

Seitenzahl

274

Maße (L/B/H)

24,1/16/2,1 cm

Gewicht

600 g

Sprache

Englisch

ISBN

978-0-387-87622-1

Beschreibung

Rezension

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)

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

02.12.2008

Abbildungen

XIV, 274 p. 100 illus.

Herausgeber

Verlag

Springer Us

Seitenzahl

274

Maße (L/B/H)

24,1/16/2,1 cm

Gewicht

600 g

Sprache

Englisch

ISBN

978-0-387-87622-1

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Genetic Programming Theory and Practice VI
  • Produktbild: Genetic Programming Theory and Practice VI
  • 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 StockSelection.- 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..