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Genetic Programming Theory and Practice X
Overview of attention for book
Table of Contents
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Book Overview
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Chapter 1
Evolving SQL Queries from Examples with Developmental Genetic Programming
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Chapter 2
A Practical Platform for On-Line Genetic Programming for Robotics
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Chapter 3
Cartesian Genetic Programming for Image Processing
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Chapter 4
A New Mutation Paradigm for Genetic Programming
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Chapter 5
Introducing an Age-Varying Fitness Estimation Function
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Chapter 6
EC-Star: A Massive-Scale, Hub and Spoke, Distributed Genetic Programming System
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Chapter 7
Genetic Analysis of Prostate Cancer Using Computational Evolution, Pareto-Optimization and Post-processing
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Chapter 8
Meta-Dimensional Analysis of Phenotypes Using the Analysis Tool for Heritable and Environmental Network Associations (ATHENA): Challenges with Building Large Networks
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Chapter 9
A Baseline Symbolic Regression Algorithm
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Chapter 10
Symbolic Regression Model Comparison Approach Using Transmitted Variation
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Chapter 11
A Framework for the Empirical Analysis of Genetic Programming System Performance
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Chapter 12
More or Less? Two Approaches to Evolving Game-Playing Strategies
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Chapter 13
Symbolic Regression Is Not Enough: It Takes a Village to Raise a Model
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Chapter 14
FlexGP.py: Prototyping Flexibly-Scaled, Flexibly-Factored Genetic Programming for the Cloud
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Chapter 15
Representing Communication and Learning in Femtocell Pilot Power Control Algorithms
Overall attention for this book and its chapters
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syllabi
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institution with syllabi
Readers on
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Mendeley
Book overview
1. Evolving SQL Queries from Examples with Developmental Genetic Programming
2. A Practical Platform for On-Line Genetic Programming for Robotics
3. Cartesian Genetic Programming for Image Processing
4. A New Mutation Paradigm for Genetic Programming
5. Introducing an Age-Varying Fitness Estimation Function
6. EC-Star: A Massive-Scale, Hub and Spoke, Distributed Genetic Programming System
7. Genetic Analysis of Prostate Cancer Using Computational Evolution, Pareto-Optimization and Post-processing
8. Meta-Dimensional Analysis of Phenotypes Using the Analysis Tool for Heritable and Environmental Network Associations (ATHENA): Challenges with Building Large Networks
9. A Baseline Symbolic Regression Algorithm
10. Symbolic Regression Model Comparison Approach Using Transmitted Variation
11. A Framework for the Empirical Analysis of Genetic Programming System Performance
12. More or Less? Two Approaches to Evolving Game-Playing Strategies
13. Symbolic Regression Is Not Enough: It Takes a Village to Raise a Model
14. FlexGP.py: Prototyping Flexibly-Scaled, Flexibly-Factored Genetic Programming for the Cloud
15. Representing Communication and Learning in Femtocell Pilot Power Control Algorithms
Summary
X
Syllabi
This data is correct as of December 2015 - for more up to date information, please visit
https://opensyllabus.org/
So far, Altmetric has seen this research output assigned in
1
syllabus from an institution on Open Syllabus Project.
Institution
Syllabi count
Course subject areas covered
University of Iowa
1
Unknown