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Genetic programming theory and pract...

Riolo, Rick.

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Genetic programming theory and practice XII

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Genetic programming theory and practice XII/ edited by Rick Riolo, William P. Worzel, Mark Kotanchek.
remainder title:	Genetic programming theory and practice 12
other author:	Riolo, Rick.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	xii, 182 p. :ill., digital ;24 cm.
[NT 15003449]:	Application of Machine-Learing Methods to Understand Gene Expression Regulation -- Identification of Novel Genetic Models of Glaucoma using the "Emergent" Genetic Programming-Based Artificial Intelligence System -- Inheritable Epigenetics in Genetic Programming -- SKGP: The Way of the Combinator -- Sequential Symbolic Regression with Genetic Programming -- Sliding Window Symbolic Regression for Detecting Changes of System Dynamics -- Extremely Accurate Symbolic Regression for Large Feature Problems -- How to Exploit Alignment in the Error Space: Two Different GP Models -- Analyzing a Decade of Human-Competitive ("HUMIE") Winners: What Can We Learn? -- Tackling the Boolean Multiplexer Function Using a Highly Distributed Genetic Programming System.
Contained By:	Springer eBooks
Subject:	Genetic programming (Computer science) -
Online resource:	http://dx.doi.org/10.1007/978-3-319-16030-6
ISBN:	9783319160306 (electronic bk.)

Genetic programming theory and practice XII
Genetic programming theory and practice XII[electronic resource] /Genetic programming theory and practice 12edited by Rick Riolo, William P. Worzel, Mark Kotanchek. - Cham :Springer International Publishing :2015. - xii, 182 p. :ill., digital ;24 cm. - Genetic and evolutionary computation,1932-0167. - Genetic and evolutionary computation..

Application of Machine-Learing Methods to Understand Gene Expression Regulation -- Identification of Novel Genetic Models of Glaucoma using the "Emergent" Genetic Programming-Based Artificial Intelligence System -- Inheritable Epigenetics in Genetic Programming -- SKGP: The Way of the Combinator -- Sequential Symbolic Regression with Genetic Programming -- Sliding Window Symbolic Regression for Detecting Changes of System Dynamics -- Extremely Accurate Symbolic Regression for Large Feature Problems -- How to Exploit Alignment in the Error Space: Two Different GP Models -- Analyzing a Decade of Human-Competitive ("HUMIE") Winners: What Can We Learn? -- Tackling the Boolean Multiplexer Function Using a Highly Distributed Genetic Programming System.

These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: gene expression regulation, novel genetic models for glaucoma, inheritable epigenetics, combinators in genetic programming, sequential symbolic regression, system dynamics, sliding window symbolic regression, large feature problems, alignment in the error space, HUMIE winners, Boolean multiplexer function, and highly distributed genetic programming systems. Application areas include chemical process control, circuit design, financial data mining and bioinformatics. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.

ISBN: 9783319160306 (electronic bk.)

Standard No.: 10.1007/978-3-319-16030-6doiSubjects--Topical Terms:

572479
Genetic programming (Computer science)

LC Class. No.: QA76.623

Dewey Class. No.: 006.3823

Genetic programming theory and practice XII
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245 0 0 $a Genetic programming theory and practice XII $h [electronic resource] / $c edited by Rick Riolo, William P. Worzel, Mark Kotanchek.
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300 $a xii, 182 p. : $b ill., digital ; $c 24 cm.
490 1 $a Genetic and evolutionary computation, $x 1932-0167
505 0 $a Application of Machine-Learing Methods to Understand Gene Expression Regulation -- Identification of Novel Genetic Models of Glaucoma using the "Emergent" Genetic Programming-Based Artificial Intelligence System -- Inheritable Epigenetics in Genetic Programming -- SKGP: The Way of the Combinator -- Sequential Symbolic Regression with Genetic Programming -- Sliding Window Symbolic Regression for Detecting Changes of System Dynamics -- Extremely Accurate Symbolic Regression for Large Feature Problems -- How to Exploit Alignment in the Error Space: Two Different GP Models -- Analyzing a Decade of Human-Competitive ("HUMIE") Winners: What Can We Learn? -- Tackling the Boolean Multiplexer Function Using a Highly Distributed Genetic Programming System.
520 $a These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: gene expression regulation, novel genetic models for glaucoma, inheritable epigenetics, combinators in genetic programming, sequential symbolic regression, system dynamics, sliding window symbolic regression, large feature problems, alignment in the error space, HUMIE winners, Boolean multiplexer function, and highly distributed genetic programming systems. Application areas include chemical process control, circuit design, financial data mining and bioinformatics. Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results.
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650 2 4 $a Algorithm Analysis and Problem Complexity. $3 891007
650 2 4 $a Programming Techniques. $3 892496
700 1 $a Riolo, Rick. $3 899500
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