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Genetic Programming

Overview of attention for book
Cover of 'Genetic Programming'

Table of Contents

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    Book Overview
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    Chapter 1 Using GP Is NEAT: Evolving Compositional Pattern Production Functions
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    Chapter 2 Evolving the Topology of Large Scale Deep Neural Networks
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    Chapter 3 Evolving Graphs by Graph Programming
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    Chapter 4 Pruning Techniques for Mixed Ensembles of Genetic Programming Models
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    Chapter 5 Analyzing Feature Importance for Metabolomics Using Genetic Programming
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    Chapter 6 Generating Redundant Features with Unsupervised Multi-tree Genetic Programming
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    Chapter 7 On the Automatic Design of a Representation for Grammar-Based Genetic Programming
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    Chapter 8 Multi-level Grammar Genetic Programming for Scheduling in Heterogeneous Networks
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    Chapter 9 Scaling Tangled Program Graphs to Visual Reinforcement Learning in ViZDoom
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    Chapter 10 Towards in Vivo Genetic Programming: Evolving Boolean Networks to Determine Cell States
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    Chapter 11 A Multiple Expression Alignment Framework for Genetic Programming
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    Chapter 12 Multi-objective Evolution of Ultra-Fast General-Purpose Hash Functions
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    Chapter 13 A Comparative Study on Crossover in Cartesian Genetic Programming
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    Chapter 14 Evolving Better RNAfold Structure Prediction
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    Chapter 15 Geometric Crossover in Syntactic Space
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    Chapter 16 Investigating a Machine Breakdown Genetic Programming Approach for Dynamic Job Shop Scheduling
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    Chapter 17 Structurally Layered Representation Learning: Towards Deep Learning Through Genetic Programming
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    Chapter 18 Comparing Rule Evaluation Metrics for the Evolutionary Discovery of Multi-relational Association Rules in the Semantic Web
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    Chapter 19 Genetic Programming Hyper-Heuristic with Cooperative Coevolution for Dynamic Flexible Job Shop Scheduling
Attention for Chapter 13: A Comparative Study on Crossover in Cartesian Genetic Programming
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Chapter title
A Comparative Study on Crossover in Cartesian Genetic Programming
Chapter number 13
Book title
Genetic Programming
Published by
Springer, Cham, April 2018
DOI 10.1007/978-3-319-77553-1_13
Book ISBNs
978-3-31-977552-4, 978-3-31-977553-1
Authors

Jakub Husa, Roman Kalkreuth

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 36%
Lecturer 2 14%
Student > Bachelor 1 7%
Other 1 7%
Student > Master 1 7%
Other 1 7%
Unknown 3 21%
Readers by discipline Count As %
Computer Science 9 64%
Engineering 2 14%
Economics, Econometrics and Finance 1 7%
Unknown 2 14%

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