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Evolutionary and Biologically Inspired Music, Sound, Art and Design

Overview of attention for book
Cover of 'Evolutionary and Biologically Inspired Music, Sound, Art and Design'

Table of Contents

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    Book Overview
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    Chapter 1 Probabilistic Decision Making for Interactive Evolution with Sensitivity Analysis
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    Chapter 2 An Interface for Fitness Function Design
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    Chapter 3 Balancing Act: Variation and Utility in Evolutionary Art
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    Chapter 4 Evolutionary and Biologically Inspired Music, Sound, Art and Design
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    Chapter 5 A Complexity Approach for Identifying Aesthetic Composite Landscapes
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    Chapter 6 Feature Construction Using Genetic Programming for Classification of Images by Aesthetic Value
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    Chapter 7 Authorship and Aesthetics Experiments: Comparison of Results between Human and Computational Systems
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    Chapter 8 An Indirect Fitness Scheme for Automated Evolution of Aesthetic Images
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    Chapter 9 A Novelty Search and Power-Law-Based Genetic Algorithm for Exploring Harmonic Spaces in J.S. Bach Chorales
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    Chapter 10 Genomic: Evolving Sound Treatments Using Genetic Algorithms
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    Chapter 11 Evolutionary and Biologically Inspired Music, Sound, Art and Design
Attention for Chapter 5: A Complexity Approach for Identifying Aesthetic Composite Landscapes
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Readers on

mendeley
6 Mendeley
Summary
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Chapter title
A Complexity Approach for Identifying Aesthetic Composite Landscapes
Chapter number 5
Book title
Evolutionary and Biologically Inspired Music, Sound, Art and Design
Published by
Springer, Berlin, Heidelberg, April 2014
DOI 10.1007/978-3-662-44335-4_5
Book ISBNs
978-3-66-244334-7, 978-3-66-244335-4
Authors

Adrian Carballal, Rebeca Perez, Antonino Santos, Luz Castro

View on publisher site
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 %
Denmark 1 17%
Unknown 5 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 50%
Professor 2 33%
Researcher 1 17%
Readers by discipline Count As %
Computer Science 5 83%
Unknown 1 17%

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