大葉大學圖書館 |

Genetic programming theory and practice XIII[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.3
書名/作者:	Genetic programming theory and practice XIII/ edited by Rick Riolo ... [et al.].
其他題名:	Genetic programming theory and practice 13
其他作者:	Riolo, Rick.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	xx, 262 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Genetic programming (Computer science) - Congresses.
標題:	Computer Science.
標題:	Artificial Intelligence (incl. Robotics)
標題:	Computational Intelligence.
標題:	Algorithm Analysis and Problem Complexity.
標題:	Operations Research, Management Science.
ISBN:	9783319342238
ISBN:	9783319342214
內容註:	Evolving Simple Symbolic Regression Models by Multi-objective Genetic Programming -- Learning Heuristics for Mining RNA Sequence-Structure Motifs -- Kaizen Programming for Feature Construction for Classification -- GP as if You Meant It: An Exercise for Mindful Practice -- nPool: Massively Distributed Simultaneous Evolution and Cross-Validation in EC-Star -- Highly Accurate Symbolic Regression with Noisy Training Data -- Using Genetic Programming for Data Science: Lessons Learned -- The Evolution of Everything (EvE) and Genetic Programming -- Lexicase selection for program synthesis: a Diversity Analysis -- Using Graph Databases to Explore the Dynamics of Genetic Programming Runs -- Predicting Product Choice with Symbolic Regression and Classification -- Multiclass Classification Through Multidimensional Clustering -- Prime-Time: Symbolic Regression takes its place in the Real World.
摘要、提要註:	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: multi-objective genetic programming, learning heuristics, Kaizen programming, Evolution of Everything (EvE), lexicase selection, behavioral program synthesis, symbolic regression with noisy training data, graph databases, and multidimensional clustering. It also covers several chapters on best practices and lesson learned from hands-on experience. Additional application areas include financial operations, genetic analysis, and predicting product choice. 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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-34223-8

Genetic programming theory and practice XIII[electronic resource] /
Genetic programming theory and practice XIII[electronic resource] /Genetic programming theory and practice 13edited by Rick Riolo ... [et al.]. - Cham :Springer International Publishing :2016. - xx, 262 p. :ill., digital ;24 cm. - Genetic and evolutionary computation,1932-0167. - Genetic and evolutionary computation..

Evolving Simple Symbolic Regression Models by Multi-objective Genetic Programming -- Learning Heuristics for Mining RNA Sequence-Structure Motifs -- Kaizen Programming for Feature Construction for Classification -- GP as if You Meant It: An Exercise for Mindful Practice -- nPool: Massively Distributed Simultaneous Evolution and Cross-Validation in EC-Star -- Highly Accurate Symbolic Regression with Noisy Training Data -- Using Genetic Programming for Data Science: Lessons Learned -- The Evolution of Everything (EvE) and Genetic Programming -- Lexicase selection for program synthesis: a Diversity Analysis -- Using Graph Databases to Explore the Dynamics of Genetic Programming Runs -- Predicting Product Choice with Symbolic Regression and Classification -- Multiclass Classification Through Multidimensional Clustering -- Prime-Time: Symbolic Regression takes its place in the Real World.

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: multi-objective genetic programming, learning heuristics, Kaizen programming, Evolution of Everything (EvE), lexicase selection, behavioral program synthesis, symbolic regression with noisy training data, graph databases, and multidimensional clustering. It also covers several chapters on best practices and lesson learned from hands-on experience. Additional application areas include financial operations, genetic analysis, and predicting product choice. 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: 9783319342238

Standard No.: 10.1007/978-3-319-34223-8doiSubjects--Topical Terms:

468983
Genetic programming (Computer science)
--Congresses.

LC Class. No.: QA76.623

Dewey Class. No.: 006.3

Genetic programming theory and practice XIII[electronic resource] /
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