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Applications of Evolutionary Computation

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Cover of 'Applications of Evolutionary Computation'

Table of Contents

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    Book Overview
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    Chapter 1 Local Fitness Meta-Models with Nearest Neighbor Regression
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    Chapter 2 Validating the Grid Diversity Operator: An Infusion Technique for Diversity Maintenance in Population-Based Optimisation Algorithms
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    Chapter 3 Benchmarking Languages for Evolutionary Algorithms
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    Chapter 4 On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front
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    Chapter 5 Evolving Smoothing Kernels for Global Optimization
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    Chapter 6 Implementing Parallel Differential Evolution on Spark
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    Chapter 7 ECJ+HADOOP: An Easy Way to Deploy Massive Runs of Evolutionary Algorithms
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    Chapter 8 Addressing High Dimensional Multi-objective Optimization Problems by Coevolutionary Islands with Overlapping Search Spaces
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    Chapter 9 Compilable Phenotypes: Speeding-Up the Evaluation of Glucose Models in Grammatical Evolution
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    Chapter 10 GPU Accelerated Molecular Docking Simulation with Genetic Algorithms
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    Chapter 11 Challenging Anti-virus Through Evolutionary Malware Obfuscation
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    Chapter 12 Leveraging Online Racing and Population Cloning in Evolutionary Multirobot Systems
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    Chapter 13 Multi-agent Behavior-Based Policy Transfer
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    Chapter 14 On-line Evolution of Foraging Behaviour in a Population of Real Robots
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    Chapter 15 Hybrid Control for a Real Swarm Robotics System in an Intruder Detection Task
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    Chapter 16 Direct Memory Schemes for Population-Based Incremental Learning in Cyclically Changing Environments
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    Chapter 17 Simheuristics for the Multiobjective Nondeterministic Firefighter Problem in a Time-Constrained Setting
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    Chapter 18 Benchmarking Dynamic Three-Dimensional Bin Packing Problems Using Discrete-Event Simulation
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    Chapter 19 Genetic Programming Algorithms for Dynamic Environments
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    Chapter 20 A Memory-Based NSGA-II Algorithm for Dynamic Multi-objective Optimization Problems
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    Chapter 21 Hybrid Dynamic Resampling Algorithms for Evolutionary Multi-objective Optimization of Invariant-Noise Problems
Attention for Chapter 19: Genetic Programming Algorithms for Dynamic Environments
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Chapter title
Genetic Programming Algorithms for Dynamic Environments
Chapter number 19
Book title
Applications of Evolutionary Computation
Published in
Lecture notes in computer science, April 2016
DOI 10.1007/978-3-319-31153-1_19
Book ISBNs
978-3-31-931152-4, 978-3-31-931153-1
Authors

João Macedo, Ernesto Costa, Lino Marques

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 45%
Student > Ph. D. Student 3 27%
Student > Doctoral Student 1 9%
Researcher 1 9%
Unknown 1 9%
Readers by discipline Count As %
Computer Science 5 45%
Biochemistry, Genetics and Molecular Biology 1 9%
Psychology 1 9%
Engineering 1 9%
Unknown 3 27%