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Exploring the Dynamic Properties of Interaction in Mixed-Initiative Procedural Content Generation
Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).ORCID-id: 0000-0002-7738-1601
2020 (Engelska)Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Malmö: Malmö universitet, 2020. , s. 237
Serie
Studies in Computer Science
Nyckelord [en]
Mixed-Initiative, Procedural Content Generation, Quality Diversity, Computer Games, Evolutionary Algorithms
Nationell ämneskategori
Datavetenskap (datalogi) Människa-datorinteraktion (interaktionsdesign)
Identifikatorer
URN: urn:nbn:se:mau:diva-18358DOI: 10.24834/isbn.9789178771400ISBN: 978-91-7877-139-4 (tryckt)ISBN: 978-91-7877-140-0 (digital)OAI: oai:DiVA.org:mau-18358DiVA, id: diva2:1471182
Presentation
2020-11-20, OR:D138, Nordenskiöldsgatan 10, Malmö, 13:00 (Engelska)
Opponent
Handledare
Tillgänglig från: 2020-09-28 Skapad: 2020-09-28 Senast uppdaterad: 2024-02-23Bibliografiskt granskad
Delarbeten
1. Fostering Creativity in the Mixed-Initiative Evolutionary Dungeon Designer
Öppna denna publikation i ny flik eller fönster >>Fostering Creativity in the Mixed-Initiative Evolutionary Dungeon Designer
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2018 (Engelska)Ingår i: Proceedings of the 13th International Conference on the Foundations of Digital Games, ACM Digital Library, 2018, artikel-id 50Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Mixed-initiative systems highlight the collaboration between humans and computers in fostering the generation of more interesting content in game design. In light of the ever-increasing cost of game development, providing mixed-initiative tools can not only significantly reduce the cost but also encourage more creativity amongst game designers. The Evolutionary Dungeon Designer (EDD) [3] is a mixed-initiative tool with a focus on using evolutionary computation to procedurally generate content that adhere to game design patterns. As part of an ongoing project, feedback from a user study on EDD's capabilities as a mixed-initiative design tool pointed out the need for improvement on the tool's functionalities [4]. In this paper we present a review of the principles of the mixed-initiative model, as well as the existing approaches that implement it. The outcome of this analysis allows us to address the appointed needs for improvement by shaping a new version of EDD that we describe here. Finally, we also present the results from a user study carried out with professional game developers, in order to assess EDD's new functionalities. Results show an overall positive evaluation of the tool's intuitiveness and capabilities for empowering game developers' creative skills during the design process of dungeons for adventure games. They also allow us to identify upcoming challenges pattern-based mixed-initiative tools could benefit from.

Ort, förlag, år, upplaga, sidor
ACM Digital Library, 2018
Nyckelord
Mixed-Initiative Design, Procedural Content Generation, Game Design Patterns
Nationell ämneskategori
Teknik och teknologier
Identifikatorer
urn:nbn:se:mau:diva-16793 (URN)10.1145/3235765.3235815 (DOI)2-s2.0-85055514392 (Scopus ID)27339 (Lokalt ID)27339 (Arkivnummer)27339 (OAI)
Konferens
International Conference on the Foundations of Digital Games, Malmö, Sweden (2018, August 7-10)
Tillgänglig från: 2020-03-30 Skapad: 2020-03-30 Senast uppdaterad: 2024-04-04Bibliografiskt granskad
2. Assessing Aesthetic Criteria in the Evolutionary dungeon Designer
Öppna denna publikation i ny flik eller fönster >>Assessing Aesthetic Criteria in the Evolutionary dungeon Designer
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2018 (Engelska)Ingår i: Proceedings of the 13th International Conference on the Foundations of Digital Games, ACM Digital Library, 2018, artikel-id 44Konferensbidrag, Publicerat paper (Refereegranskat)
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.

Ort, förlag, år, upplaga, sidor
ACM Digital Library, 2018
Serie
International Conference Proceeding Series (ICPS)
Nyckelord
Procedural Content Generation, Evolutionary Algorithms, Mixed-Initiative Design
Nationell ämneskategori
Teknik och teknologier
Identifikatorer
urn:nbn:se:mau:diva-16819 (URN)10.1145/3235765.3235810 (DOI)2-s2.0-85055581467 (Scopus ID)27341 (Lokalt ID)27341 (Arkivnummer)27341 (OAI)
Konferens
International Conference on the Foundations of Digital Games, Malmö, Sweden (2018, August 7-10)
Tillgänglig från: 2020-03-30 Skapad: 2020-03-30 Senast uppdaterad: 2024-02-05Bibliografiskt granskad
3. Empowering Quality Diversity in Dungeon Design with Interactive Constrained MAP-Elites
Öppna denna publikation i ny flik eller fönster >>Empowering Quality Diversity in Dungeon Design with Interactive Constrained MAP-Elites
2019 (Engelska)Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

We propose the use of quality-diversity algorithms for mixed-initiative game content generation. This idea is implemented as a new feature of the Evolutionary Dungeon Designer, a system for mixed-initiative design of the type of levels you typically find in computer role playing games. The feature uses the MAP-Elites algorithm, an illumination algorithm which divides the population into a number of cells depending on their values along several behavioral dimensions. Users can flexibly and dynamically choose relevant dimensions of variation, and incorporate suggestions produced by the algorithm in their map designs. At the same time, any modifications performed by the human feed back into MAP-Elites, and are used to generate further suggestions.

Ort, förlag, år, upplaga, sidor
IEEE, 2019
Serie
IEEE Conference on Computational Intelligence and Games, ISSN 2325-4270, E-ISSN 2325-4289
Nyckelord
Procedural Content Generation, Evolutionary Algorithms, MIxed-Initiative Co-Creativity, Computer Games
Nationell ämneskategori
Teknik och teknologier
Identifikatorer
urn:nbn:se:mau:diva-12640 (URN)10.1109/CIG.2019.8848022 (DOI)000843154300065 ()2-s2.0-85073116656 (Scopus ID)30472 (Lokalt ID)30472 (Arkivnummer)30472 (OAI)
Konferens
IEEE Conference on Games, London, United Kingdom (2019/08/20 - 2019/08/23)
Tillgänglig från: 2020-02-29 Skapad: 2020-02-29 Senast uppdaterad: 2023-12-14Bibliografiskt granskad
4. Perceived Behaviors of Personality-Driven Agents
Öppna denna publikation i ny flik eller fönster >>Perceived Behaviors of Personality-Driven Agents
2019 (Engelska)Ingår i: Violence - Perception - Video Games: New Directions in Game Research / [ed] Federico Alvarez Igarzábal, Michael S. Debus, Curtis L. Maughan, Transcript Verlag, 2019, s. 171-184Kapitel i bok, del av antologi (Refereegranskat)
Ort, förlag, år, upplaga, sidor
Transcript Verlag, 2019
Serie
Bild und Bit : Studies of digital media culture, ISSN 2702-8240, E-ISSN 2702-8259
Nationell ämneskategori
Människa-datorinteraktion (interaktionsdesign) Datavetenskap (datalogi)
Identifikatorer
urn:nbn:se:mau:diva-18277 (URN)10.14361/9783839450512-015 (DOI)2-s2.0-85124557944 (Scopus ID)9783839450512 (ISBN)
Tillgänglig från: 2020-09-21 Skapad: 2020-09-21 Senast uppdaterad: 2023-12-20Bibliografiskt granskad
5. Learning the Designer’s Preferences to Drive Evolution
Öppna denna publikation i ny flik eller fönster >>Learning the Designer’s Preferences to Drive Evolution
2020 (Engelska)Ingår i: EvoApplications 2020: Applications of Evolutionary Computation, Springer, 2020, s. 431-445Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

This paper presents the Designer Preference Model, a data-driven solution that pursues to learn from user generated data in a Quality-Diversity Mixed-Initiative Co-Creativity (QD MI-CC) tool, with the aims of modelling the user’s design style to better assess the tool’s procedurally generated content with respect to that user’s preferences. Through this approach, we aim for increasing the user’s agency over the generated content in a way that neither stalls the user-tool reciprocal stimuli loop nor fatigues the user with periodical suggestion handpicking. We describe the details of this novel solution, as well as its implementation in the MI-CC tool the Evolutionary Dungeon Designer. We present and discuss our findings out of the initial tests carried out, spotting the open challenges for this combined line of research that integrates MI-CC with Procedural Content Generation through Machine Learning.

Ort, förlag, år, upplaga, sidor
Springer, 2020
Serie
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 12104
Nyckelord
Procedural Content Generation, Machine Learning, Mixed-initiative Co-Creativity, Evolutionary Computation
Nationell ämneskategori
Människa-datorinteraktion (interaktionsdesign) Datavetenskap (datalogi)
Forskningsämne
Interaktionsdesign
Identifikatorer
urn:nbn:se:mau:diva-18273 (URN)10.1007/978-3-030-43722-0_28 (DOI)000896394100028 ()2-s2.0-85084747634 (Scopus ID)978-3-030-43722-0 (ISBN)978-3-030-43721-3 (ISBN)
Konferens
Applications of Evolutionary Computation, 15-17 April 2020, Seville, Spain
Tillgänglig från: 2020-09-21 Skapad: 2020-09-21 Senast uppdaterad: 2023-12-14Bibliografiskt granskad
6. Toward Designer Modeling Through Design Style Clustering
Öppna denna publikation i ny flik eller fönster >>Toward Designer Modeling Through Design Style Clustering
2022 (Engelska)Ingår i: IEEE Transactions on Games, ISSN 2475-1502, Vol. 14, nr 4, s. 676-686Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

We propose modeling designer style in mixed-initiative game content creation tools as archetypical design traces. These design traces are formulated as transitions between design styles; these design styles are in turn found through clustering all intermediate designs along the way to making a complete design. This method is implemented in the Evolutionary Dungeon Designer, a research platform for mixed-initiative systems to create adventure and dungeon crawler games. We present results both in the form of design styles for rooms, which can be analyzed to better understand the kind of rooms designed by users, and in the form of archetypical sequences between these rooms, i.e., Designer Personas.

Ort, förlag, år, upplaga, sidor
IEEE, 2022
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
urn:nbn:se:mau:diva-51543 (URN)10.1109/tg.2022.3143800 (DOI)000908822400014 ()2-s2.0-85123365921 (Scopus ID)
Tillgänglig från: 2022-05-19 Skapad: 2022-05-19 Senast uppdaterad: 2024-02-05Bibliografiskt granskad

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