University of Sussex
Browse

File(s) not publicly available

A Fitness Function for Creativity in Jazz Improvisation and Beyond

presentation
posted on 2023-06-08, 07:15 authored by Anna Jordanous
Can a computer evolve creative entities based on how creative they are? Taking the domain of jazz improvisation, this ongoing work investigates how creativity can be evolved and evaluated by a computational system. The aim is for the system to work with minimal human assistance, as autonomously as possible. The system employs a genetic algorithm to evolve musical parameters for algorithmic jazz music improvisation. For each set of parameters, several improvisations are generated. The fitness function of the genetic algorithm implements a set of criteria for creativity proposed by Graeme Ritchie. The evolution of the improvisation parameters is directed by the creativity demonstrated in the generated improvisations. From preliminary findings, whilst Ritchie's criteria does guide the system towards producing more acceptably pleasing and typical jazz music, the criteria (in their current form) rely too heavily on human intervention to be practically useful for computational evaluation of creativity. In pursuing more autonomous creativity assessment, however, this system is a promising testbed for examining alternative theories about how creativity could be evaluated computationally.

History

Publication status

  • Published

Presentation Type

  • paper

Event name

Proceedings of the First International Conference on Computational Creativity (ICCCX)

Event location

Lisbon, Portugal

Event type

conference

Department affiliated with

  • Informatics Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2012-02-06

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC