On Collaborator Selection in Creative Agent Societies: An Evolutionary Art Case Study

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We study how artistically creative agents may learn to select favorable collaboration partners. We consider a society of creative agents with varying skills and aesthetic preferences able to interact with each other by exchanging artifacts or through collaboration. The agents exhibit interaction awareness by modeling their peers and make decisions about collaboration based on the learned peer models. To test the peer models, we devise an experimental collaboration process for evolutionary art, where two agents create an artifact by evolving the same artifact set in turns. In an empirical evaluation, we focus on how effective peer models are in selecting collaboration partners and compare the results to a baseline where agents select collaboration partners randomly. We observe that peer models guide the agents to more beneficial collaborations.

Titel på värdpublikationComputational Intelligence in Music, Sound, Art and Design : 7th International Conference, EvoMUSART 2018, Parma, Italy, April 4-6, 2018, Proceedings
RedaktörerAntonios Liapis, Juan Jesús Romero Cardalda, Anikó Ekárt
Antal sidor17
FörlagSpringer International Publishing AG
Utgivningsdatum4 apr. 2018
ISBN (tryckt)978-3-319-77582-1
ISBN (elektroniskt)978-3-319-77583-8
StatusPublicerad - 4 apr. 2018
MoE-publikationstypA4 Artikel i en konferenspublikation
EvenemangInternational Conference on Computational Intelligence in Music, Sound, Art and Design - Parma, Italien
Varaktighet: 4 apr. 20186 apr. 2018
Konferensnummer: 7


NamnLecture Notes in Computer Science
FörlagSpringer International Publishing AG
ISSN (tryckt)0302-9743
ISSN (elektroniskt)1611-3349


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