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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 Evolving High-Level Imperative Program Trees with Strongly Formed Genetic Programming
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    Chapter 2 Android Genetic Programming Framework
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    Chapter 3 Genetic Programming for Generalised Helicopter Hovering Control
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    Chapter 4 Cartesian Genetic Programming for Memristive Logic Circuits
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    Chapter 5 Genetic Programming
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    Chapter 6 Medial Crossovers for Genetic Programming
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    Chapter 7 Improving Face Detection
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    Chapter 8 Genetic Programming
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    Chapter 9 Improving Relevance Measures Using Genetic Programming
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    Chapter 10 An Investigation of Fitness Sharing with Semantic and Syntactic Distance Metrics
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    Chapter 11 Evolving Reusable Operation-Based Due-Date Assignment Models for Job Shop Scheduling with Genetic Programming
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    Chapter 12 Genetic Programming
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    Chapter 13 Multi-Objective Ant Programming for Mining Classification Rules
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    Chapter 14 Matrix Analysis of Genetic Programming Mutation
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    Chapter 15 An Ecological Approach to Measuring Locality in Linear Genotype to Phenotype Maps
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    Chapter 16 Coevolution in Cartesian Genetic Programming
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    Chapter 17 Evolutionary Design of Message Efficient Secrecy Amplification Protocols
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    Chapter 18 Automatic Design of Ant Algorithms with Grammatical Evolution
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    Chapter 19 Random Sampling Technique for Overfitting Control in Genetic Programming
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    Chapter 20 Evolutionary Operator Self-adaptation with Diverse Operators
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    Chapter 21 The Effect of Bloat on the Efficiency of Incremental Evolution of Simulated Snake-Like Robot
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    Chapter 22 Bayesian Network Structure Learning from Limited Datasets through Graph Evolution
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    Chapter 23 Efficient Phenotype Evaluation in Cartesian Genetic Programming
Overall attention for this book and its chapters
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Citations

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Title
Genetic Programming
Published by
Lecture notes in computer science, January 2012
DOI 10.1007/978-3-642-29139-5
ISBNs
978-3-64-229138-8, 978-3-64-229139-5
Authors

Alberto Moraglio, Sara Silva, Krzysztof Krawiec, Penousal Machado, Carlos Cotta

Editors

Moraglio, Alberto, Silva, Sara, Krawiec, Krzysztof, Machado, Penousal, Cotta, Carlos, Moraglio, Alberto, Silva, Sara, Krawiec, Krzysztof, Machado, Penousal, Cotta, Carlos

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 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 50%
Student > Ph. D. Student 2 33%
Professor > Associate Professor 1 17%
Readers by discipline Count As %
Engineering 3 50%
Unspecified 1 17%
Computer Science 1 17%
Business, Management and Accounting 1 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 December 2016.
All research outputs
#20,705,128
of 23,305,591 outputs
Outputs from Lecture notes in computer science
#7,032
of 8,163 outputs
Outputs of similar age
#223,761
of 246,589 outputs
Outputs of similar age from Lecture notes in computer science
#451
of 491 outputs
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So far Altmetric has tracked 8,163 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 491 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.