Advertisement

Evolutionary and Biologically Inspired Music, Sound, Art and Design

Second International Conference, EvoMUSART 2013, Vienna, Austria, April 3-5, 2013. Proceedings

  • Penousal Machado
  • James McDermott
  • Adrian Carballal

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7834)

Table of contents

  1. Front Matter
  2. Jon McCormack
    Pages 1-12
  3. Brigitte Rafael, Michael Affenzeller, Stefan Wagner
    Pages 13-24
  4. Maximos A. Kaliakatsos–Papakostas, Andreas Floros, Michael N. Vrahatis
    Pages 25-36
  5. Vic Ciesielski, Perry Barile, Karen Trist
    Pages 47-58
  6. Jonathan Eisenmann, Matthew Lewis, Rick Parent
    Pages 72-84
  7. Mohammad Majid al-Rifaie, John Mark Bishop
    Pages 85-96
  8. Mohammad Majid al-Rifaie, John Mark Bishop
    Pages 97-108
  9. Eelco den Heijer
    Pages 109-120
  10. Mario García-Valdez, Leonardo Trujillo, Francisco Fernández de Vega, Juan Julián Merelo Guervós, Gustavo Olague
    Pages 121-132
  11. João Correia, Penousal Machado, Juan Romero, Adrian Carballal
    Pages 133-144
  12. Shihui Guo, Safa Tharib, Jian Chang, Jianjun Zhang
    Pages 145-156
  13. Malik Nairat, Palle Dahlstedt, Mats G. Nordahl
    Pages 168-179
  14. Antonios Liapis, Georgios N. Yannakakis, Julian Togelius
    Pages 180-191
  15. Back Matter

About these proceedings

Introduction

This book constitutes the refereed proceedings of the Second International Conference on Biologically Inspired Music, Sound, Art and Design, EvoMUSART 2013, held in Vienna, Austria, in March 2013, colocated with the Evo* 2013 events EuroGP, EvoCOP, EvoBIO, and EvoApplications.
The 11 revised full papers and 5 poster papers presented were carefully reviewed and selected from 36 submissions. They cover a wide range of topics and application areas, including: generative approaches to music, graphics, game content, and narrative; robot gait creation; music information retrieval; computational aesthetics; the mechanics of interactive evolutionary computation; and the art theory of evolutionary computation.

Keywords

aesthetic measures evolutionary algorithms genetic algorithms machine learning particle swarm optimization

Editors and affiliations

  • Penousal Machado
    • 1
  • James McDermott
    • 2
  • Adrian Carballal
    • 3
  1. 1.Faculty of Sciences and Technology, Department of Informatics EngineeringUniversity of CoimbraCoimbraPortugal
  2. 2.Quinn Business SchoolUniversity College DublinDonnybrookIreland
  3. 3.School of Computer Science, Department of Communications and Information TechnologiesUniversity of A CoruñaA CoruñaSpain

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-36955-1
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-36954-4
  • Online ISBN 978-3-642-36955-1
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
Industry Sectors
Pharma
Automotive
Finance, Business & Banking
Electronics
IT & Software
Telecommunications
Consumer Packaged Goods
Aerospace