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Genetic Programming : 17th European Conference, EuroGP 2014, Granada, Spain, April 23-25, 2014, Revised Selected Papers

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Cover of 'Genetic Programming : 17th European Conference, EuroGP 2014, Granada, Spain, April 23-25, 2014, Revised Selected Papers'

Table of Contents

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    Book Overview
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    Chapter 1 Higher Order Functions for Kernel Regression
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    Chapter 2 Flash: A GP-GPU Ensemble Learning System for Handling Large Datasets
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    Chapter 3 Learning Dynamical Systems Using Standard Symbolic Regression
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    Chapter 4 Semantic Crossover Based on the Partial Derivative Error
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    Chapter 5 A Multi-dimensional Genetic Programming Approach for Multi-class Classification Problems
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    Chapter 6 Generalisation Enhancement via Input Space Transformation: A GP Approach
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    Chapter 7 On Diversity, Teaming, and Hierarchical Policies: Observations from the Keepaway Soccer Task
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    Chapter 8 Genetic Programming
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    Chapter 9 Measuring Mutation Operators’ Exploration-Exploitation Behaviour and Long-Term Biases
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    Chapter 10 Exploring the Search Space of Hardware / Software Embedded Systems by Means of GP
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    Chapter 11 Enhancing Branch-and-Bound Algorithms for Order Acceptance and Scheduling with Genetic Programming
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    Chapter 12 Using Genetic Improvement and Code Transplants to Specialise a C++ Program to a Problem Class
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    Chapter 13 ESAGP – A Semantic GP Framework Based on Alignment in the Error Space
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    Chapter 14 Building a Stage 1 Computer Aided Detector for Breast Cancer Using Genetic Programming
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    Chapter 15 NEAT, There’s No Bloat
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    Chapter 16 The Best Things Don’t Always Come in Small Packages: Constant Creation in Grammatical Evolution
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    Chapter 17 Asynchronous Evolution by Reference-Based Evaluation: Tertiary Parent Selection and Its Archive
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    Chapter 18 Behavioral Search Drivers for Genetic Programing
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    Chapter 19 Cartesian Genetic Programming: Why No Bloat?
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    Chapter 20 On Evolution of Multi-category Pattern Classifiers Suitable for Embedded Systems
Attention for Chapter 11: Enhancing Branch-and-Bound Algorithms for Order Acceptance and Scheduling with Genetic Programming
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Chapter title
Enhancing Branch-and-Bound Algorithms for Order Acceptance and Scheduling with Genetic Programming
Chapter number 11
Book title
Genetic Programming
Published by
Springer, Berlin, Heidelberg, April 2014
DOI 10.1007/978-3-662-44303-3_11
Book ISBNs
978-3-66-244302-6, 978-3-66-244303-3
Authors

Su Nguyen, Mengjie Zhang, Mark Johnston, Nguyen, Su, Zhang, Mengjie, Johnston, Mark

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 33%
Student > Master 2 22%
Professor > Associate Professor 2 22%
Researcher 1 11%
Student > Doctoral Student 1 11%
Other 0 0%
Readers by discipline Count As %
Computer Science 4 44%
Biochemistry, Genetics and Molecular Biology 1 11%
Physics and Astronomy 1 11%
Engineering 1 11%
Unknown 2 22%