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Computational Intelligence in Music, Sound, Art and Design

Overview of attention for book
Cover of 'Computational Intelligence in Music, Sound, Art and Design'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Algorithmic Songwriting with ALYSIA
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    Chapter 2 On Symmetry, Aesthetics and Quantifying Symmetrical Complexity
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    Chapter 3 Towards Polyphony Reconstruction Using Multidimensional Multiple Sequence Alignment
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    Chapter 4 Melody Retrieval and Classification Using Biologically-Inspired Techniques
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    Chapter 5 Evolved Aesthetic Analogies to Improve Artistic Experience
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    Chapter 6 Deep Artificial Composer: A Creative Neural Network Model for Automated Melody Generation
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    Chapter 7 A Kind of Bio-inspired Learning of mUsic stylE
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    Chapter 8 Using Autonomous Agents to Improvise Music Compositions in Real-Time
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    Chapter 9 Generating Polyphonic Music Using Tied Parallel Networks
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    Chapter 10 Mixed-Initiative Creative Drawing with webIconoscope
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    Chapter 11 Clustering Agents for the Evolution of Autonomous Musical Fitness
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    Chapter 12 EvoFashion: Customising Fashion Through Evolution
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    Chapter 13 A Swarm Environment for Experimental Performance and Improvisation
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    Chapter 14 Niche Constructing Drawing Robots
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    Chapter 15 Automated Shape Design by Grammatical Evolution
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    Chapter 16 Evolutionary Image Transition Using Random Walks
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    Chapter 17 Evaluation Rules for Evolutionary Generation of Drum Patterns in Jazz Solos
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    Chapter 18 Assessing Augmented Creativity: Putting a Lovelace Machine for Interactive Title Generation Through a Human Creativity Test
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    Chapter 19 Play it Again: Evolved Audio Effects and Synthesizer Programming
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    Chapter 20 Fashion Design Aid System with Application of Interactive Genetic Algorithms
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    Chapter 21 Generalisation Performance of Western Instrument Recognition Models in Polyphonic Mixtures with Ethnic Samples
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    Chapter 22 Exploring the Exactitudes Portrait Series with Restricted Boltzmann Machines
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    Chapter 23 Evolving Mondrian-Style Artworks
  25. Altmetric Badge
    Chapter 24 Predicting Expressive Bow Controls for Violin and Viola
Attention for Chapter 8: Using Autonomous Agents to Improvise Music Compositions in Real-Time
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About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 X user

Citations

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5 Dimensions

Readers on

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15 Mendeley
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Chapter title
Using Autonomous Agents to Improvise Music Compositions in Real-Time
Chapter number 8
Book title
Computational Intelligence in Music, Sound, Art and Design
Published in
Lecture notes in computer science, March 2017
DOI 10.1007/978-3-319-55750-2_8
Book ISBNs
978-3-31-955749-6, 978-3-31-955750-2
Authors

Patrick Hutchings, Jon McCormack

X Demographics

X Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 7%
Unknown 14 93%

Demographic breakdown

Readers by professional status Count As %
Other 2 13%
Student > Doctoral Student 2 13%
Student > Bachelor 2 13%
Student > Ph. D. Student 2 13%
Student > Master 2 13%
Other 5 33%
Readers by discipline Count As %
Computer Science 9 60%
Arts and Humanities 2 13%
Agricultural and Biological Sciences 1 7%
Psychology 1 7%
Social Sciences 1 7%
Other 0 0%
Unknown 1 7%
Attention Score in Context

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 16 April 2017.
All research outputs
#15,453,139
of 22,963,381 outputs
Outputs from Lecture notes in computer science
#4,658
of 8,137 outputs
Outputs of similar age
#194,596
of 309,330 outputs
Outputs of similar age from Lecture notes in computer science
#42
of 103 outputs
Altmetric has tracked 22,963,381 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,137 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 309,330 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.