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Genetic programming theory and pract...

(1998 :)

Genetic programming theory and practice XIV

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Genetic programming theory and practice XIVedited by Rick Riolo ... [et al.].
其他題名:	Genetic programming theory and practice 14
其他作者:	Riolo, Rick.
團體作者:
出版者:	Cham :Springer International Publishing :2018.
面頁冊數:	xv, 227 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Genetic programming (Computer science)
電子資源:	https://doi.org/10.1007/978-3-319-97088-2
ISBN:	9783319970882$q(electronic bk.)

Genetic programming theory and practice XIV
Genetic programming theory and practice XIV[electronic resource] /Genetic programming theory and practice 14edited by Rick Riolo ... [et al.]. - Cham :Springer International Publishing :2018. - xv, 227 p. :ill., digital ;24 cm. - Genetic and evolutionary computation,1932-0167. - Genetic and evolutionary computation..

1 Similarity-based Analysis of Population Dynamics in Genetic Programming Performing Symbolic Regression -- 2 An Investigation of Hybrid Structural and Behavioral Diversity Methods in Genetic Programming -- 3 Investigating Multi-Population Competitive Coevolution for Anticipation of Tax Evasion -- 4 Evolving Artificial General Intelligence for Video Game Controllers -- 5 A Detailed Analysis of a PushGP Run -- 6 Linear Genomes for Structured Programs -- 7 Neutrality, Robustness, and Evolvability in Genetic Programming -- 8 Local Search is Underused in Genetic Programming -- 9 PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification -- 10 Discovering Relational Structural in Program Synthesis Problems with Analogical Reasoning -- 11 An Evolutionary Algorithm for Big Data Multi-Class Classification Problems -- 12 A Genetic Framework for Building Dispersion Operators in the Semantic Space -- 13 Assisting Asset Model Development with Evolutionary Augmentation -- 14 Identifying and Harnessing the Building Blocks of Machine Learning Pipelines for Sensible Initialization of a Data Science Automation Tool.

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. Chapters in this volume include: Similarity-based Analysis of Population Dynamics in GP Performing Symbolic Regression Hybrid Structural and Behavioral Diversity Methods in GP Multi-Population Competitive Coevolution for Anticipation of Tax Evasion Evolving Artificial General Intelligence for Video Game Controllers A Detailed Analysis of a PushGP Run Linear Genomes for Structured Programs Neutrality, Robustness, and Evolvability in GP Local Search in GP PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification Relational Structure in Program Synthesis Problems with Analogical Reasoning An Evolutionary Algorithm for Big Data Multi-Class Classification Problems A Generic Framework for Building Dispersion Operators in the Semantic Space Assisting Asset Model Development with Evolutionary Augmentation Building Blocks of Machine Learning Pipelines for Initialization of a Data Science Automation Tool 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: 9783319970882$q(electronic bk.)

Standard No.: 10.1007/978-3-319-97088-2doiSubjects--Topical Terms:

206263
Genetic programming (Computer science)

LC Class. No.: QA76.623

Dewey Class. No.: 006.31

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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. Chapters in this volume include: Similarity-based Analysis of Population Dynamics in GP Performing Symbolic Regression Hybrid Structural and Behavioral Diversity Methods in GP Multi-Population Competitive Coevolution for Anticipation of Tax Evasion Evolving Artificial General Intelligence for Video Game Controllers A Detailed Analysis of a PushGP Run Linear Genomes for Structured Programs Neutrality, Robustness, and Evolvability in GP Local Search in GP PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification Relational Structure in Program Synthesis Problems with Analogical Reasoning An Evolutionary Algorithm for Big Data Multi-Class Classification Problems A Generic Framework for Building Dispersion Operators in the Semantic Space Assisting Asset Model Development with Evolutionary Augmentation Building Blocks of Machine Learning Pipelines for Initialization of a Data Science Automation Tool 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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