Creativity and Markov Decision Processes

Creativity is already regularly attributed to AI systems outside specialised computational creativity (CC) communities. However, the evaluation of creativity in AI at large typically lacks grounding in creativity theory, which can promote inappropriate attributions and limit the analysis of creative behaviour. While CC researchers have translated psychological theory into formal models, the value of these models is limited by a gap to common AI frameworks. To mitigate this limitation, we identify formal mappings between Boden's process theory of creativity and Markov Decision Processes (MDPs), using the Creative Systems Framework as a stepping stone. We study three out of eleven mappings in detail to understand which types of creative processes, opportunities for (aberrations), and threats to creativity (uninspiration) could be observed in an MDP. We conclude by discussing quality criteria for the selection of such mappings for future work and applications.

Citation

Lahikainen, J, Ady, N M & Guckelsberger, C 2024, Creativity and Markov Decision Processes. in K Grace, M T Llano, P Martins & M Hedblom (eds), Proceedings of the 15th International Conference on Computational Creativity (ICCC 2024). Association for Computational Creativity, International Conference on Computational Creativity, Jönköping, Sweden, 17/06/2024. < https://arxiv.org/abs/2405.14966 >

Permanent link to this item

https://urn.fi/URN:NBN:fi:aalto-202412117680

Collections

[article-cris] Perustieteiden korkeakoulu / SCI

Show all metadata

Creativity and Markov Decision Processes

Access rights

URL

Journal Title

Journal ISSN

Volume Title

Authors

Date

Department

Major/Subject

Mcode

Degree programme

Language

Pages

Series

Abstract

Description

Keywords

Other note

Citation

Permanent link to this item

Collections