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Natural computing algorithms

Brabazon, Anthony.

Natural computing algorithms

Record Type:	Electronic resources : Monograph/item
Title/Author:	Natural computing algorithmsby Anthony Brabazon, Michael O'Neill, Sean McGarraghy.
Author:	Brabazon, Anthony.
other author:	O'Neill, Michael.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg :2015.
Description:	xx, 554 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Natural computation.
Online resource:	http://dx.doi.org/10.1007/978-3-662-43631-8
ISBN:	9783662436318$q(electronic bk.)

Natural computing algorithms
Brabazon, Anthony.

Natural computing algorithms[electronic resource] /by Anthony Brabazon, Michael O'Neill, Sean McGarraghy. - Berlin, Heidelberg :Springer Berlin Heidelberg :2015. - xx, 554 p. :ill., digital ;24 cm. - Natural computing series,1619-7127. - Natural computing series..

Introduction -- Introduction to Evolutionary Computing -- Genetic Algorithms -- Extending the Genetic Algorithm -- Evolution Strategies and Evolutionary Programming -- Differential Evolution -- Genetic Programming -- Particle Swarm Algorithms -- Ant Algorithms -- Honeybee Algorithms -- Other Social Algorithms -- Bacterial Foraging Algorithms -- Neural Networks for Supervised Learning -- Neural Networks for Unsupervised Learning -- Neuroevolution -- Artificial Immune Systems -- An Introduction to Developmental and Grammatical Computing -- Grammar-Based and Developmental Genetic Programming -- Grammatical Evolution -- TAG3P and Developmental TAG3P -- Genetic Regulatory Networks -- An Introduction to Physics-Inspired Computing -- Physics-Inspired Computing Algorithms -- Quantum-Inspired Evolutionary Algorithms -- Plant-Inspired Algorithms -- Chemistry-Inspired Algorithms -- Conclusions -- References -- Index.

The field of natural computing has been the focus of a substantial research effort in recent decades. One particular strand of this research concerns the development of computational algorithms using metaphorical inspiration from systems and phenomena that occur in the natural world. These naturally inspired computing algorithms have proven to be successful problem-solvers across domains as diverse as management science, bioinformatics, finance, marketing, engineering, architecture and design. This book is a comprehensive introduction to natural computing algorithms, suitable for academic and industrial researchers and for undergraduate and graduate courses on natural computing in computer science, engineering and management science.

ISBN: 9783662436318$q(electronic bk.)

Standard No.: 10.1007/978-3-662-43631-8doiSubjects--Topical Terms:

339160
Natural computation.

LC Class. No.: QA76.9.N37

Dewey Class. No.: 006.38

Natural computing algorithms
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505 0 $a Introduction -- Introduction to Evolutionary Computing -- Genetic Algorithms -- Extending the Genetic Algorithm -- Evolution Strategies and Evolutionary Programming -- Differential Evolution -- Genetic Programming -- Particle Swarm Algorithms -- Ant Algorithms -- Honeybee Algorithms -- Other Social Algorithms -- Bacterial Foraging Algorithms -- Neural Networks for Supervised Learning -- Neural Networks for Unsupervised Learning -- Neuroevolution -- Artificial Immune Systems -- An Introduction to Developmental and Grammatical Computing -- Grammar-Based and Developmental Genetic Programming -- Grammatical Evolution -- TAG3P and Developmental TAG3P -- Genetic Regulatory Networks -- An Introduction to Physics-Inspired Computing -- Physics-Inspired Computing Algorithms -- Quantum-Inspired Evolutionary Algorithms -- Plant-Inspired Algorithms -- Chemistry-Inspired Algorithms -- Conclusions -- References -- Index.
520 $a The field of natural computing has been the focus of a substantial research effort in recent decades. One particular strand of this research concerns the development of computational algorithms using metaphorical inspiration from systems and phenomena that occur in the natural world. These naturally inspired computing algorithms have proven to be successful problem-solvers across domains as diverse as management science, bioinformatics, finance, marketing, engineering, architecture and design. This book is a comprehensive introduction to natural computing algorithms, suitable for academic and industrial researchers and for undergraduate and graduate courses on natural computing in computer science, engineering and management science.
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