GenMuse: An Evolutionary Creativity Enhancement Tool

Massimo Salomoni, Jenny Carter

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)


Creativity is often defined as the creation of something novel through the use of imagination. But for all artists, creativity is also the exploration of new and unknown areas within their specific art. Is it possible to stimulate creativity through a system that creates inspiring original music, and that is also able to learn the personal tastes of its user?
Within the project, an evolutionary approach was used in an attempt to stimulate musical creativity by supplying a composer with software that can compose short musical patterns called riffs. The software, called GenMuse, evolves populations of riffs, and makes use of a feed-forward artificial neural network to learn how to autonomously evaluate the evolved riffs to satisfy the tastes of the composer.
The results show that the approach is worthy of further investigation. The genetic algorithm produced interesting results that, according to our evaluation parameters, could be included “as is” in a musical composition, and the neural network was able to evaluate the riffs with a good success ratio.
Original languageEnglish
Title of host publicationArtificial Intelligence XXXVI
Subtitle of host publication39th SGAI International Conference on Artificial Intelligence, AI 2019, Cambridge, UK, December 17–19, 2019, Proceedings
EditorsMax Bramer, Miltos Petridis
Place of PublicationCham
PublisherSpringer, Cham
Number of pages12
VolumeLNAI 11927
ISBN (Electronic)9783030348854
ISBN (Print)9783030348847
Publication statusPublished - 19 Nov 2019
Event39th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence - Peterhouse College, Cambridge, Cambridge, United Kingdom
Duration: 17 Dec 201919 Dec 2019
Conference number: 39

Publication series

NameLecture Notes in Computer Science/Lecture Notes in Artificial Intelligence
VolumeLNCS 11927/LNAI 11927
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference39th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence
Abbreviated titleAI 2019
Country/TerritoryUnited Kingdom
Internet address


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