The 13th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART) 2024 is a multidisciplinary conference that brings together researchers who are working on the application of Artificial Intelligence techniques in creative and artistic 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 been 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 here.
- Colin Johnson
University of Nottingham, United Kingdom
- Sérgio Rebelo
University of Coimbra, Portugal
- Iria Santos
Universidade da Coruña, Spain
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:
- 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.
- 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;
- Contextualisation of creative AI in cultural, economic, social, political or ecological discourse.
- 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.
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.
Follow these instructions to submit a paper.
The acceptance rate at EvoMUSART 2023 was 36% for papers accepted for long talks and 13% for short talks.