Genetic programming theory and practice XI /

Genetic programming theory and practice XI /

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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: evo...

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Bibliographic Details
Other Authors: Kotanchek, Mark (Editor), Moore, Jason H. (Editor), Riolo, Rick (Editor)
Format: Book
Language:English
Published: New York, NY : Springer, 2014
Series:Genetic and evolutionary computation series
Subjects:
Genetic programming (Computer science)
COMPUTERS > General
algorithms
algoritmen
artificial intelligence
computational science
computer analysis
computer sciences
computer techniques
computeranalyse
computertechnieken
computerwetenschappen
kunstmatige intelligentie
programmeren
programming
Informatie- en communicatietechnologie (algemeen)
Information and Communication Technology (General)
Electronic books
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245 0 0 |a Genetic programming theory and practice XI /  |c Rick Riolo, Jason H. Moore, Mark Kotanchek, editors ; foreword by Arthur K. Kordon 
246 3 |a Genetic programming theory and practice 11 
264 1 |a New York, NY :  |b Springer,  |c 2014 
300 |a 1 online resource (240 pages) :  |b 36 black and white illustrations 
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490 1 |a Genetic and evolutionary computation 
504 |a Includes bibliographical references at the end of each chapters and index 
505 0 |a Extreme Accuracy in Symbolic Regression -- Exploring Interestingness in a Computational Evolution System for the Genome-Wide Genetic Analysis of Alzheimer's Disease -- Optimizing a Cloud Contract Portfolio using Genetic Programming-based Load Models -- Maintenance of a Long Running Distributed Genetic Programming System for Solving Problems Requiring Big Data -- Grounded Simulation: Using Simulated Evolution to Guide Embodied Evolution -- Applying Genetic Programming in Business Forecasting -- Explaining Unemployment Rates with Symbolic Regression -- Uniform Linear Transformation with Repair and Alternation in Genetic Programming -- A Deterministic and Symbolic Regression Hybrid Applied to Resting-State fMRI Data -- Gaining Deeper Insights in Symbolic Regression -- Geometric Semantic Genetic Programming for Real Life Applications -- Evaluation of Parameter Contribution to Neural Network Size and Fitness in ATHENA for Genetic Analysis 
508 |a Foreword by Arthur K. Kordon 
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: 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 
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700 1 |a Kotanchek, Mark,  |e editor 
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700 1 |a Moore, Jason H.,  |e editor 
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700 1 |a Riolo, Rick,  |e editor 
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