| 1. |
- Alvarez, Alberto, 1992-
(författare)
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Exploring Game Design through Human-AI Collaboration
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 2. |
- Eladhari, Mirjam P, 1971-, et al.
(författare)
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Interweaving Story Coherence and Player Creativity through Story-Making Games
- 2014
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Ingår i: Interactive Storytelling. - Cham : Springer International Publishing. - 9783319123363 - 9783319123370 ; , s. 73-80
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In story-making games, players create stories together by using narrative tokens. Often there is a tension between players playing to win using the rules of a story-making game, and collaboratively creating a good story. In this paper, we introduce a competitive story-making game prototype coupled with computational methods intended to be used for both supporting players’ creativity and narrative coherence.
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| 3. |
- Liapis, Antonios, et al.
(författare)
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Mixed-media Game AI
- 2018
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Ingår i: Dagstuhl Reports. - : Schloss Dagstuhl Leibniz-Zentrum für Informatik GmbH. - 2192-5283. ; 7:11, s. 105-107
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 4. |
- Togelius, Julian, et al.
(författare)
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Controllable procedural map generation via multiobjective evolution
- 2013
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Ingår i: Genetic Programming and Evolvable Machines. - : Springer Science and Business Media LLC. - 1389-2576 .- 1573-7632. ; 14:2, s. 245-277
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Tidskriftsartikel (refereegranskat)abstract
- This paper shows how multiobjective evolutionary algorithms can be used to procedurally generate complete and playable maps for real-time strategy (RTS) games. We devise heuristic objective functions that measure properties of maps that impact important aspects of gameplay experience. To show the generality of our approach, we design two different evolvable map representations, one for an imaginary generic strategy game based on heightmaps, and one for the classic RTS game StarCraft. The effect of combining tuples or triples of the objective functions are investigated in systematic experiments, in particular which of the objectives are partially conflicting. A selection of generated maps are visually evaluated by a population of skilled StarCraft players, confirming that most of our objectives correspond to perceived gameplay qualities. Our method could be used to completely automate in-game controlled map generation, enabling player-adaptive games, or as a design support tool for human designers.
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| 5. |
- Togelius, Julian, et al.
(författare)
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Multiobjective Exploration of the StarCraft Map Space
- 2010
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Ingår i: 2010 IEEE Symposium on Computational Intelligence and Games (CIG). - Copenhagen : IEEE conference proceedings. ; , s. 265-272
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Konferensbidrag (refereegranskat)abstract
- This paper presents a search-based method for generating maps for the popular real-time strategy (RTS) game StarCraft. We devise a representation of StarCraft maps suitable for evolutionary search, along with a set of fitness functions based on predicted entertainment value of those maps, as derived from theories of player experience. A multiobjective evolutionary algorithm is then used to evolve complete Star- Craft maps based on the representation and selected fitness functions. The output of this algorithm is a Pareto front approximation visualizing the tradeoff between the several fitness functions used, and where each point on the front represents a viable map. We argue that this method is useful for both automatic and machine-assisted map generation, and in particular that the Pareto fronts are excellent design support tools for human map designers.
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