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Springer Linear Genetic Programming - Evolutionary Computation

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Description

Explore a unique approach to evolutionary computation with Linear Genetic Programming by Springer. Unlike traditional methods that use syntax trees or functional expressions, this book examines a variant of Genetic Programming that evolves imperative computer programs as linear sequences of instructions. This text provides a deep investigation into typical GP phenomena, including non-effective code, neutral variations, and code growth, specifically from the perspective of linear GP. Designed as a comprehensive reference for researchers, it also contains sufficient introductory material to support students and newcomers entering the field. It is an essential resource for those studying mathematics and higher education topics within science and nature.

Key Features

This Springer publication presents a variant of Genetic Programming that evolves imperative computer programs using linear sequences of instructions.

The text investigates typical GP phenomena such as code growth, neutral variations, and non-effective code through the lens of linear GP.

Designed as a reference for researchers, this book provides detailed analysis of evolutionary computation methods.

Includes introductory material suitable for students and newcomers to the field of Genetic and Evolutionary Computation.

This book is categorized under Mathematics for Higher Education within the Science, Nature and Maths subject area.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
29 November 2010
Listed Since
14 June 2010

Barcode

No barcode data available

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