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Assessing the Effects of Interacting with MAP-Elites
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-7738-1601
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0003-3924-7484
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-2644-2785
New York University.
2021 (English)In: Proceedings of the seventeenth {AAAI} Conference on Artificial Intelligence and Interactive Digital Entertainment, Association for the Advancement of Artificial Intelligence , 2021, Vol. 17, p. 124-131Conference paper, Published paper (Refereed)
Abstract [en]

MAP-Elites has been successfully applied to the generation of game content and robot behaviors. However, its behavior and performance when interacted with in co-creative systems is underexplored. This paper analyzes the implications of synthetic interaction for the stability and adaptability of MAP-Elites in such scenarios. We use pre-recorded human-made level design sessions with the Interactive Constrained MAP-Elites (IC MAP-Elites). To analyze the effect of each edition step in the search space over time using different feature dimensions, we introduce Temporal Expressive Range Analysis (TERA). With TERAs, MAP-Elites is assessed in terms of its adaptability and stability to generate diverse and high-performing individuals. Our results show that interactivity, in the form of design edits and MAP-Elites adapting towards them, directs the search process to previously unexplored areas of the fitness landscape and points towards how this could improve and enrich the co-creative process with quality-diverse individuals.

Place, publisher, year, edition, pages
Association for the Advancement of Artificial Intelligence , 2021. Vol. 17, p. 124-131
Series
Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, ISSN 2326-909X, E-ISSN 2334-0924 ; 17:1
National Category
Computer Sciences Human Computer Interaction
Research subject
Interaktionsdesign
Identifiers
URN: urn:nbn:se:mau:diva-47273DOI: 10.1609/aiide.v17i1.18899Scopus ID: 2-s2.0-85129807455ISBN: 978-1-57735-871-8 (print)OAI: oai:DiVA.org:mau-47273DiVA, id: diva2:1617705
Conference
Artificial Intelligence and Interactive Digital Entertainment (AIIDE), October 11–15, 2021, A Virtual Conference
Available from: 2021-12-07 Created: 2021-12-07 Last updated: 2024-12-05Bibliographically approved
In thesis
1. Exploring Game Design through Human-AI Collaboration
Open this publication in new window or tab >>Exploring Game Design through Human-AI Collaboration
2022 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Game design is a hard and multi-faceted task that intertwines different gameplay mechanics, audio, level, graphic, and narrative facets. Games' facets are developed in conjunction with others with a common goal that makes games coherent and interesting. These combinations result in plenty of games in diverse genres, which usually require a collaboration of a diverse group of designers. Collaborators can take different roles and support each other with their strengths resulting in games with unique characteristics. The multi-faceted nature of games and their collaborative properties and requirements make it an exciting task to use Artificial Intelligence (AI). The generation of these facets together requires a holistic approach, which is one of the most challenging tasks within computational creativity. Given the collaborative aspect of games, this thesis approaches their generation through Human-AI collaboration, specifically using a mixed-initiative co-creative (MI-CC) paradigm. This paradigm creates an interactive and collaborative scenario that leverages AI and human strengths with an alternating and proactive initiative to approach a task. However, this paradigm introduces several challenges, such as Human and AI goal alignment or competing properties.

In this thesis, game design and the generation of game facets by themselves and intertwined are explored through Human-AI collaboration. The AI takes a colleague's role with the designer, arising multiple dynamics, challenges, and opportunities. The main hypothesis is that AI can be incorporated into systems as a collaborator, enhancing design tools, fostering human creativity, and reducing workload. The challenges and opportunities that arise from this are explored, discussed, and approached throughout the thesis. As a result, multiple approaches and methods such as quality-diversity algorithms and designer modeling are proposed to generate game facets in tandem with humans, create a better workflow, enhance the interaction, and establish adaptive experiences.

Place, publisher, year, edition, pages
Malmö: Malmö universitet, 2022. p. 381
Series
Studies in Computer Science ; 20
Keywords
Computer Games, Human-AI Collaboration, Mixed-Initiative, Procedural Content Generation, Quality Diversity, Computational Creativity
National Category
Computer Sciences Human Computer Interaction
Research subject
Interaktionsdesign
Identifiers
urn:nbn:se:mau:diva-54586 (URN)10.24834/isbn.9789178773084 (DOI)978-91-7877-307-7 (ISBN)978-91-7877-308-4 (ISBN)
Public defence
2022-09-27, Niagara hörsal C, Nordenskiöldsgatan 1, 21119, Malmö, 14:30 (English)
Opponent
Supervisors
Available from: 2022-08-29 Created: 2022-08-27 Last updated: 2022-12-08Bibliographically approved

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Alvarez, AlbertoFont, JoseDahlskog, Steve

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