Franklin

Genetic Programming Theory and Practice XIV [electronic resource] / edited by Rick Riolo, Bill Worzel, Brian Goldman, Bill Tozier.

Edition:
1st ed. 2018.
Publication:
Cham : Springer International Publishing : Imprint: Springer, 2018.
Series:
Computer Science (Springer-11645)
Genetic and evolutionary computation series 1932-0167
Genetic and Evolutionary Computation, 1932-0167
Format/Description:
Book
1 online resource (XV, 227 pages) : 52 illustrations
Subjects:
Artificial intelligence.
Computational intelligence.
Algorithms.
Local subjects:
Artificial Intelligence. (search)
Computational Intelligence. (search)
Algorithm Analysis and Problem Complexity. (search)
System Details:
text file PDF
Summary:
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.
Contents:
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.
Contributor:
Riolo, Rick, editor., Editor,
Worzel, Bill, editor., Editor,
Goldman, Brian, editor., Editor,
Tozier, Bill. editor., Editor,
SpringerLink (Online service)
Contained In:
Springer eBooks
Other format:
Printed edition:
Printed edition:
Printed edition:
ISBN:
978-3-319-97088-2
9783319970882
9783319970875 (Printed edition)
9783319970899 (Printed edition)
9783030073008 (Printed edition)
Publisher Number:
10.1007/978-3-319-97088-2 doi
Access Restriction:
Restricted for use by site license.
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