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Genetic Programming

Overview of attention for book
Cover of 'Genetic Programming'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 802.11 De-authentication Attack Detection Using Genetic Programming
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    Chapter 2 A Divide & Conquer Strategy for Improving Efficiency and Probability of Success in Genetic Programming
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    Chapter 3 A Genetic Programming Approach to Solomonoff’s Probabilistic Induction
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    Chapter 4 A Less Destructive, Context-Aware Crossover Operator for GP
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    Chapter 5 AQUAGP: Approximate QUery Answers Using Genetic Programming
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    Chapter 6 Blindbuilder: A New Encoding to Evolve Lego-Like Structures
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    Chapter 7 Dynamic Scheduling with Genetic Programming
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    Chapter 8 Emergent Generality of Adapted Locomotion Gaits of Simulated Snake-Like Robot
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    Chapter 9 Evolving Crossover Operators for Function Optimization
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    Chapter 10 Genetic Programming, Validation Sets, and Parsimony Pressure
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    Chapter 11 Genetic Programming
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    Chapter 12 Incentive Method to Handle Constraints in Evolutionary Algorithms with a Case Study
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    Chapter 13 Iterative Filter Generation Using Genetic Programming
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    Chapter 14 Iterative Prototype Optimisation with Evolved Improvement Steps
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    Chapter 15 Learning Recursive Functions with Object Oriented Genetic Programming
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    Chapter 16 Negative Slope Coefficient: A Measure to Characterize Genetic Programming Fitness Landscapes
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    Chapter 17 Population Clustering in Genetic Programming
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    Chapter 18 Projecting Financial Data Using Genetic Programming in Classification and Regression Tasks
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    Chapter 19 Solving Sudoku with the GAuGE System
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    Chapter 20 The Halting Probability in Von Neumann Architectures
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    Chapter 21 Using Subtree Crossover Distance to Investigate Genetic Programming Dynamics
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    Chapter 22 Characterizing Diversity in Genetic Programming
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    Chapter 23 Genetic Programming
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    Chapter 24 Design of Robust Communication Systems Using Genetic Algorithms
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    Chapter 25 Developmental Evaluation in Genetic Programming: The Preliminary Results
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    Chapter 26 Evolving Noisy Oscillatory Dynamics in Genetic Regulatory Networks
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    Chapter 27 Information-Dependent Switching of Identification Criteria in a Genetic Programming System for System Identification
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    Chapter 28 Genetic Programming
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    Chapter 29 On the Locality of Grammatical Evolution
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    Chapter 30 Optimizing the Initialization of Dynamic Decision Heuristics in DPLL SAT Solvers Using Genetic Programming
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    Chapter 31 P-CAGE: An Environment for Evolutionary Computation in Peer-to-Peer Systems
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    Chapter 32 Positional Independence and Recombination in Cartesian Genetic Programming
Attention for Chapter 19: Solving Sudoku with the GAuGE System
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Citations

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Chapter title
Solving Sudoku with the GAuGE System
Chapter number 19
Book title
Genetic Programming
Published in
Lecture notes in computer science, April 2006
DOI 10.1007/11729976_19
Book ISBNs
978-3-54-033143-8, 978-3-54-033144-5
Authors

Nicolau, Miguel, Ryan, Conor, Miguel Nicolau, Conor Ryan

Twitter Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 8%
Italy 1 4%
Chile 1 4%
Colombia 1 4%
United States 1 4%
Unknown 18 75%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 29%
Researcher 5 21%
Professor > Associate Professor 4 17%
Student > Ph. D. Student 4 17%
Student > Bachelor 1 4%
Other 1 4%
Unknown 2 8%
Readers by discipline Count As %
Computer Science 15 63%
Engineering 3 13%
Business, Management and Accounting 1 4%
Medicine and Dentistry 1 4%
Biochemistry, Genetics and Molecular Biology 1 4%
Other 0 0%
Unknown 3 13%

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 06 February 2017.
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#7,507,133
of 9,738,454 outputs
Outputs from Lecture notes in computer science
#5,352
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#224,744
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Outputs of similar age from Lecture notes in computer science
#71
of 98 outputs
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