The 12th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART) 2023 is a multidisciplinary conference that brings together researchers who are working on the application of Artificial Intelligence techniques in creative and artist fields.

There is a growing interest in the application of Artificial Neural Networks, Evolutionary Computation, Swarm Intelligence, Cellular Automata, Alife, and other Artificial Intelligence techniques in fields such as: visual art and music generation, analysis, and interpretation; sound synthesis; architecture; video; poetry; design; and other creative tasks. Therefore, the use of Artificial Intelligence in such creative domains became a significant and exciting area of research. EvoMUSART provides the opportunity to present, discuss and promote innovative contributions and ongoing work in the area. 

Following the success of previous events and the importance of the field of Artificial Intelligence applied to music, sound, art and design, EvoMUSART has become an evo* conference with independent proceedings since 2012. The EvoMUSART proceedings have been published in Springer Lecture Notes in Computer Science (LNCS).

Download the CFP in PDF.

NEW: The proceedings of EvoMUSART 2023 are available following this link.

Conference Chairs

  • Colin Johnson
    University of Nottingham, United Kingdom
    Colin.Johnson(at)nottingham.ac.uk
  • Nereida Rodríguez-Fernández
    University of A Coruña, Spain
    nereida.rodriguezf(at)udc.es

Publication Chair

  • Sérgio Rebelo
    University of Coimbra, Portugal
    srebelo(at)dei.uc.pt

Areas of Interest and Contributions

Submissions should concern the use of Artificial Intelligence techniques (e.g. Evolutionary Computation, Artificial Neural Networks, Artificial Life, Machine Learning, Deep Learning, Swarm Intelligence) in the generation, analysis and interpretation of art, music, design, architecture and other creative and artistic fields. Topics of interest include, but are not limited to:

Generation

  • Systems that create drawings, images, animations, sculptures, poetry, text, designs, webpages, buildings, etc.;
  • Systems that create musical pieces, sounds, instruments, voices, sound effects, sound analysis, etc.;
  • Systems that create artefacts such as game content, architecture, furniture, based on aesthetic and functional criteria;
  • Robotic-based Evolutionary Art and Music;
  • Other related artificial intelligence or generative techniques in the fields of Computer Music, Computer Art, etc.

Automation

  • Techniques for automatic fitness assignment;
  • Systems in which an analysis or interpretation of the artworks is used in conjunction with artificial intelligence techniques to produce novel objects;
  • Systems that resort to artificial intelligence approaches to perform the analysis of image, music, sound, sculpture, or some other types of artistic object or resource.

Computer Aided Creativity and Computational Creativity

  • Systems in which artificial intelligence is used to promote the creativity of a human user;
  • New ways of integrating the user in the evolutionary cycle;
  • Analysis and evaluation of: the artistic potential of biologically inspired art and music; the artistic processes inherent to these approaches; the resulting artefacts;
  • Collaborative distributed artificial art environments.

Theory

  • Computational Aesthetics, Experimental Aesthetics; Emotional Response, Surprise, Novelty;
  • Representation techniques;
  • Surveys of the current state-of-the-art in the area; identification of weaknesses and strengths; comparative analysis and classification;
  • Validation methodologies;
  • Studies on the applicability of these techniques to related areas;
  • New models designed to promote the creative potential of biologically inspired computation.

EvoMUSART Index

The EvoMUSART Index gathers the information on all EvoMUSART papers since 2003. The idea is to bring together all the publications in a handy web page that allows the visitors to navigate through all papers, best papers, authors, keywords, and years of the conference while providing quick access to Springer’s web page links. Feel free to explore, search and bookmark this web page.

Submission Details

Accepted papers will be presented orally or as posters at the event and included in the evo* proceedings, published by Springer Nature in a dedicated volume of the Lecture Notes in Computer Science series. Submissions will be rigorously reviewed for scientific and artistic merit. Submitters are strongly encouraged to provide in all papers a link for download of media demonstrating their results, whether music, images, video, or other media types. The reviewing process will be double-blind, so please omit information about the authors in the submitted paper and anonymise links for double-blind review. Submissions must be at most 16 A4 pages long, in Springer LNCS format.

Paper limit: 16 pages

Submission link: https://easychair.org/conferences/?conf=evo2023

The authors of accepted papers will have to improve their papers based on the reviewers’ comments and will be asked to send a camera-ready version of their manuscripts (notifications will be sent on 18 January, 2023 and the camera-ready deadline will be on 1 February, 2023). At least one author of each accepted work has to register for the conference no later than 27 February 2023, attend the conference and present the work. The acceptance rate at EvoMUSART 2022 was 41% for papers accepted for long talks and 11% for short talks.

Programme Committee

Mauro Annunziato, ENEA
Peter Bentley, University College London
Gilberto Bernardes, University of Porto
Ulysses Bernardet, Aston University
Daniel Bisig, Zurich University of the Arts
Tim Blackwell, Goldsmiths, University of London
Jean-Pierre Briot, Sorbonne University & Pontifical Catholic University of Rio de Janeiro
Andrew Brown, Griffith University
Marcelo Caetano, McGill University
Amilcar Cardoso, University of Coimbra
Luz Castro Pena, University of A Coruña
Vic Ciesielski, RMIT University
Simon Colton, Queen Mary University of London
Michael Cook, Falmouth University
João Correia, University of Coimbra
Pedro M. Cruz, Northeastern University
Camilo Cruz Gambardella, Monash University
João Miguel Cunha, University of Coimbra
Hans Dehlinger, University of Kassel
Georgios Diapoulis, Chalmers University of Technology
Edward Easton, Aston University
Arne Eigenfeldt, Simon Fraser University
Frederic Fol Leymarie, Goldsmiths, University of London
José Fornari, University of Campinas
Philip Galanter, Texas A&M University
Björn Gambäck, Norwegian University of Science and Technology
Pablo Gervás, Universidad Complutense de Madrid
Carlos Grilo, Polytechnic of Leiria
Andrew Horner, The Hong Kong University of Science and Technology
Takashi Ikegami, University of Tokyo
Anna Jordanous, University of Kent
Man Hei Law, The Hong Kong University of Science and Technology
Carlos León, Universidad Complutense de Madrid
John P. Lewis, Weta Digital, Victoria University
Matthew Lewis, Ohio State University
Antonios Liapis, University of Malta
Alain Lioret, Paris Diderot University
Roisin Loughran, University College Dublin
Penousal Machado, University of Coimbra
Bill Manaris, College of Charleston
Tiago Martins, University of Coimbra
Jon McCormack, Monash University
Rolando Miragaia, Polytechnic of Leiria
Eduardo Miranda, University of Plymouth
Nicolas Monmarché, University François Rabelais of Tours
María Navarro, University of Salamanca
Aneta Neumann, University of Adelaide
Michael O’Neill, University College Dublin
Somnuk Phon-Amnuaisuk, Universiti Teknologi Brunei
Jane Prophet, University of Michigan
Brian Ross, Brock University
Jonathan E. Rowe, University of Birmingham
Antonino Santos, University of A Coruña
Iria Santos, University of A Coruña
Marco Scirea, University of Southern Denmark
Daniel Silva, University of Porto
Luis Teixeira, Fraunhofer AICOS
Stephen Todd, Goldsmiths, University of London
Paulo Urbano, University of Lisbon
Anna Ursyn, University of Northern Colorado
Igor Vatolkin, TU Dortmund University
Sebastian von Mammen, Julius-Maximilians University Würzburg