Genetic Programming Theory and Practice X (Genetic and Evolutionary Computation)

ISBN 10: 1461468450 / ISBN 13: 9781461468455

Published by Springer, 2013

About this Item

Used - Like New. Book is new and unread but may have minor shelf wear. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. Seller Inventory # Z1-C-027-01628

Bibliographic Details

Title: Genetic Programming Theory and Practice X (...

Publisher: Springer

Publication Date: 2013

Binding: Hardcover

Condition: Like New

About this title

Synopsis:

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: evolutionary constraints, relaxation of selection mechanisms, diversity preservation strategies, flexing fitness evaluation, evolution in dynamic environments, multi-objective and multi-modal selection, foundations of evolvability, evolvable and adaptive evolutionary operators, foundation of  injecting expert knowledge in evolutionary search, analysis of problem difficulty and required GP algorithm complexity, foundations in running GP on the cloud – communication, cooperation, flexible implementation, and ensemble methods. Additional focal points for GP symbolic regression are: (1) The need to guarantee convergence to solutions in the function discovery mode; (2) Issues on model validation; (3) The need for model analysis workflows for insight generation based on generated GP solutions – model exploration, visualization, variable selection, dimensionality analysis; (4) Issues in combining different types of data.

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.

Review:

From the book reviews:

“This book reflects the progress made in GP during recent years. It covers a large range of up-to-date applications and theoretical issues. All of the papers are valuable and are recommended reading for AI scientists or novices.” (Svetlana Segarceanu, Computing Reviews, July, 2014)