| 1. |
- Alvarez, Alberto, 1992-, et al.
(författare)
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Assessing Aesthetic Criteria in the Evolutionary dungeon Designer
- 2018
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Ingår i: Proceedings of the 13th International Conference on the Foundations of Digital Games. - New York, NY, USA : ACM Digital Library.
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 2. |
- Alvarez, Alberto, 1992-, et al.
(författare)
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Assessing the Effects of Interacting with MAP-Elites
- 2021
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Ingår i: Proceedings of the seventeenth {AAAI} Conference on Artificial Intelligence and Interactive Digital Entertainment. - : Association for the Advancement of Artificial Intelligence. - 9781577358718 ; , s. 124-131
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 3. |
- Alvarez, Alberto, 1992-, et al.
(författare)
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Empowering Quality Diversity in Dungeon Design with Interactive Constrained MAP-Elites
- 2019
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 4. |
- 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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| 5. |
- Alvarez, Alberto, 1992-
(författare)
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Exploring the Dynamic Properties of Interaction in Mixed-Initiative Procedural Content Generation
- 2020
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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| 6. |
- Alvarez, Alberto, 1992-, et al.
(författare)
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Fostering Creativity in the Mixed-Initiative Evolutionary Dungeon Designer
- 2018
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Ingår i: Proceedings of the 13th International Conference on the Foundations of Digital Games. - New York, NY, USA : ACM Digital Library.
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 7. |
- Alvarez, Alberto, 1992-, et al.
(författare)
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Interactive Constrained MAP-Elites : Analysis and Evaluation of the Expressiveness of the Feature Dimensions
- 2022
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Ingår i: IEEE Transactions on Games. - : IEEE. - 2475-1502 .- 2475-1510. ; 14:2, s. 202-211
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Tidskriftsartikel (refereegranskat)abstract
- We propose the Interactive Constrained MAP-Elites, a quality-diversity solution for game content generation, implemented as a new feature of the Evolutionary Dungeon Designer (EDD): a mixed-initiative co-creativity tool for designing dungeons. The feature uses the MAP-Elites algorithm, an illumination algorithm that segregates the population among several cells depending on their scores with respect to different behavioral dimensions. Users can flexibly and dynamically alternate between these dimensions anytime, thus guiding the evolutionary process in an intuitive way, and then incorporate suggestions produced by the algorithm in their room designs. At the same time, any modifications performed by the human user will feed back into MAP-Elites, closing a circular workflow of constant mutual inspiration. This paper presents the algorithm followed by an in-depth evaluation of the expressive range of all possible dimension combinations in several scenarios, and discusses their influence in the fitness landscape and in the overall performance of the procedural content generation in EDD.
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| 8. |
- Baldwin, Alexander, et al.
(författare)
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Mixed-initiative procedural generation of dungeons using game design patterns
- 2017
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Ingår i: Proceedings of the 2017 IEEE Conference on Computational Intelligence and Games (CIG). - : IEEE. ; , s. 25-32
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Konferensbidrag (refereegranskat)abstract
- Abstract: Procedural Content Generation (PCG) can be a useful tool for aiding creativity in the process of designing game levels. Mixed-initiative level generation tools where a designer and an algorithm collaborate to iteratively generate game levels have been used for this purpose. However, it can be difficult for designers to work with tools that do not respond to the common language of games: game design patterns. We present the Evolutionary Dungeon Designer, the first step towards a mixed-initiative dungeon design tool which evolves dungeon rooms using game design patterns, as well as several metrics regarding the placement of treasures and enemies, in the fitness function of a genetic algorithm. Our results show that we are able to control the frequency, shape and type of design patterns, as well as properly place enemies and treasures in the generated rooms, using design pattern-related input parameters.
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| 9. |
- Baldwin, Alexander, et al.
(författare)
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Towards Pattern-Based Mixed-Initiative Dungeon Generation
- 2017
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Ingår i: Proceedings of the 12th International Conference on the Foundations of Digital Games;12. - New York, NY, USA : ACM Digital Library.
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Konferensbidrag (refereegranskat)abstract
- Mixed-initiative Procedural Content Generation uses algorithms to assist human designers in the collaborative creation of game content. Different mixed-initiative approaches use different methods to engage with the design material while supporting the designer’s intentions. However, the designer runs the risk of misunderstanding the system’s abilities and how to control them. In order to limit miscommunication during the design process, heuristics could be applied. In this paper we present a mixed-initiative tool for evolving dungeons with the aid of game design patterns as heuristics. The tool, the Evolutionary Dungeon Designer, uses a genetic algorithm that searches for levels containing game design patterns on two hierarchical levels of abstraction to express more complex gameplay in the game level. We evaluate the tool through a series of lab experiments and a user study conducted with professional game developers. Our results demonstrate that we are able to control the generation of the different patterns with the aid of design pattern-related input parameters, as well as identifying a number of features a design pattern-based mixed-initiative tool could benefit from.
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| 10. |
- Dahlskog, Steve, et al.
(författare)
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A multi-level level generator
- 2014
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Konferensbidrag (refereegranskat)abstract
- Generating content at multiple levels of abstraction simultaneously is an open challenge in procedural content generation. Representing and automatically replicating the style of a human designer is another. This paper addresses both of these challenges through extending a previously devised methodology for pattern-based level generation. This method builds on an analysis of Super Mario Bros levels into three abstraction levels: micro-, meso- and macro-patterns. Micro-patterns are then used as building blocks in a search-based PCG approach that searches for macro-patterns, which are defined as combinations of meso-patterns. Results show that we can successfully generate levels that replicate the macro-patterns of selected input levels, and we argue that this constitutes an approach to automatically analysing and replicating style in level design.
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