Editors:
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10198)
Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)
Conference series link(s): EvoMUSART: International Conference on Computational Intelligence in Music, Sound, Art and Design (Part of EvoStar)
Conference proceedings info: EvoMUSART 2017.
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Table of contents (24 papers)
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Front Matter
About this book
The 24 revised full papers presented were carefully reviewed and selected from 29 submissions. The papers cover a wide range of topics and application areas, including: generative approaches to music, graphics, game content, and narrative; music information retrieval; computational aesthetics; the mechanics of interactive evolutionary computation; computer-aided design; and the art theory of evolutionary computation.
Keywords
- algorithms
- distributed systems
- genetic algorithms
- information retrieval
- swarm intelligence
- agents
- ant colony optimization
- applications
- bioinformatics
- classification
- evolutionary algorithm
- genetic programming
- heuristics
- image analysis
- machine learning
- multi-agent systems
- neural networks
- sequence alignment
- software engineering
- theoretical computer science
Editors and Affiliations
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University of Coimbra , Coimbra, Portugal
João Correia
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RMIT University , Melbourne, Australia
Vic Ciesielski
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University of Malta , Msida, Malta
Antonios Liapis
Bibliographic Information
Book Title: Computational Intelligence in Music, Sound, Art and Design
Book Subtitle: 6th International Conference, EvoMUSART 2017, Amsterdam, The Netherlands, April 19–21, 2017, Proceedings
Editors: João Correia, Vic Ciesielski, Antonios Liapis
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-319-55750-2
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2017
Softcover ISBN: 978-3-319-55749-6Published: 22 March 2017
eBook ISBN: 978-3-319-55750-2Published: 03 April 2017
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: X, 371
Number of Illustrations: 169 b/w illustrations
Topics: Algorithm Analysis and Problem Complexity, Data Mining and Knowledge Discovery, Artificial Intelligence, Image Processing and Computer Vision, Probability and Statistics in Computer Science, Computer Appl. in Arts and Humanities