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Genetic Programming

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Cover of 'Genetic Programming'

Table of Contents

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    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 22: Characterizing Diversity in Genetic Programming
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Chapter title
Characterizing Diversity in Genetic Programming
Chapter number 22
Book title
Genetic Programming
Published by
Springer, Berlin, Heidelberg, April 2006
DOI 10.1007/11729976_22
Book ISBNs
978-3-54-033143-8, 978-3-54-033144-5

Bart Wyns, Peter De Bruyne, Luc Boullart

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 6%
Netherlands 1 6%
Italy 1 6%
Unknown 14 82%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 29%
Researcher 4 24%
Student > Master 4 24%
Professor > Associate Professor 2 12%
Student > Bachelor 1 6%
Other 1 6%
Readers by discipline Count As %
Computer Science 12 71%
Biochemistry, Genetics and Molecular Biology 1 6%
Business, Management and Accounting 1 6%
Medicine and Dentistry 1 6%
Engineering 1 6%
Other 0 0%
Unknown 1 6%