Publikationer från Malmö universitet
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Assessing Aesthetic Criteria in the Evolutionary dungeon Designer
Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).ORCID-id: 0000-0002-7738-1601
Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).ORCID-id: 0000-0002-2644-2785
Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).ORCID-id: 0000-0003-3924-7484
Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).ORCID-id: 0000-0002-7701-0851
Vise andre og tillknytning
2018 (engelsk)Inngår i: Proceedings of the 13th International Conference on the Foundations of Digital Games, ACM Digital Library, 2018, artikkel-id 44Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The Evolutionary Dungeon Designer (EDD) [1] is as a mixed-initiative tool for creating dungeons for adventure games. Results from a user study with game developers positively evaluated EDD as a suitable framework for collaboration between human designers and PCG suggestions, highlighting these as time-saving and inspiring for creating dungeons [2]. Previous work on EDD identified the need of assessing aesthetic criteria as a key area for improvement in its PCG Engine. By upgrading the individual encoding system and the fitness evaluation in EDD's evolutionary algorithm, we present three techniques to preserve and account the designer's aesthetic criteria during the dungeon generation process: the capability of locking sections for preserving custom aesthetic structures, as well as the measurement of symmetry and similarity in the provided suggestions.

sted, utgiver, år, opplag, sider
ACM Digital Library, 2018. artikkel-id 44
Serie
International Conference Proceeding Series (ICPS)
Emneord [en]
Procedural Content Generation, Evolutionary Algorithms, Mixed-Initiative Design
HSV kategori
Identifikatorer
URN: urn:nbn:se:mau:diva-16819DOI: 10.1145/3235765.3235810Scopus ID: 2-s2.0-85055581467Lokal ID: 27341OAI: oai:DiVA.org:mau-16819DiVA, id: diva2:1420333
Konferanse
International Conference on the Foundations of Digital Games, Malmö, Sweden (2018, August 7-10)
Tilgjengelig fra: 2020-03-30 Laget: 2020-03-30 Sist oppdatert: 2024-02-05bibliografisk kontrollert
Inngår i avhandling
1. Exploring the Dynamic Properties of Interaction in Mixed-Initiative Procedural Content Generation
Åpne denne publikasjonen i ny fane eller vindu >>Exploring the Dynamic Properties of Interaction in Mixed-Initiative Procedural Content Generation
2020 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
Abstract [en]

As AI develops, grows, and expands, the more benefits we can have from it. AI is used in multiple fields to assist humans, such as object recognition, self-driving cars, or design tools. However, AI could be used for more than assisting humans in their tasks. It could be employed to collaborate with humans as colleagues in shared tasks, which is usually described as Mixed-Initiative (MI) paradigm. This paradigm creates an interactive scenario that leverage on AI and human strengths with an alternating and proactive initiative to approach a task. However, this paradigm introduces several challenges. For instance, there must be an understanding between humans and AI, where autonomy and initiative become negotiation tokens. In addition, control and expressiveness need to be taken into account to reach some goals. Moreover, although this paradigm has a broader application, it is especially interesting for creative tasks such as games, which are mainly created in collaboration. Creating games and their content is a hard and complex task, since games are content-intensive, multi-faceted, and interacted by external users. 

Therefore, this thesis explores MI collaboration between human game designers and AI for the co-creation of games, where the AI's role is that of a colleague with the designer. The main hypothesis is that AI can be incorporated in systems as a collaborator, enhancing design tools, fostering human creativity, reducing their workload, and creating adaptive experiences. Furthermore, This collaboration arises several dynamic properties such as control, expressiveness, and initiative, which are all central to this thesis. Quality-Diversity algorithms combined with control mechanisms and interactions for the designer are proposed to investigate this collaboration and properties. Designer and Player modeling is also explored, and several approaches are proposed to create a better workflow, establish adaptive experiences, and enhance the interaction. Through this, it is demonstrated the potential and benefits of these algorithms and models in the MI paradigm.

sted, utgiver, år, opplag, sider
Malmö: Malmö universitet, 2020. s. 237
Serie
Studies in Computer Science
Emneord
Mixed-Initiative, Procedural Content Generation, Quality Diversity, Computer Games, Evolutionary Algorithms
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-18358 (URN)10.24834/isbn.9789178771400 (DOI)978-91-7877-139-4 (ISBN)978-91-7877-140-0 (ISBN)
Presentation
2020-11-20, OR:D138, Nordenskiöldsgatan 10, Malmö, 13:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2020-09-28 Laget: 2020-09-28 Sist oppdatert: 2024-02-23bibliografisk kontrollert
2. Exploring Game Design through Human-AI Collaboration
Åpne denne publikasjonen i ny fane eller vindu >>Exploring Game Design through Human-AI Collaboration
2022 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
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.

sted, utgiver, år, opplag, sider
Malmö: Malmö universitet, 2022. s. 381
Serie
Studies in Computer Science ; 20
Emneord
Computer Games, Human-AI Collaboration, Mixed-Initiative, Procedural Content Generation, Quality Diversity, Computational Creativity
HSV kategori
Forskningsprogram
Interaktionsdesign
Identifikatorer
urn:nbn:se:mau:diva-54586 (URN)10.24834/isbn.9789178773084 (DOI)978-91-7877-307-7 (ISBN)978-91-7877-308-4 (ISBN)
Disputas
2022-09-27, Niagara hörsal C, Nordenskiöldsgatan 1, 21119, Malmö, 14:30 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2022-08-29 Laget: 2022-08-27 Sist oppdatert: 2022-12-08bibliografisk kontrollert

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