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A Comparative Evaluation of Procedural Level Generators in the Mario AI Framework
Malmö högskola, School of Technology (TS).ORCID iD: 0000-0002-2644-2785
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2014 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Evaluation is an open problem in procedural content generation research. The eld is now in a state where there is a glut of content generators, each serving di erent purposes and using a variety of techniques. It is difficult to understand, quantitatively or qualitatively, what makes one generator di erent from another in terms of its output. To remedy this, we have conducted a large-scale comparative evaluation of level generators for the Mario AI Benchmark, a research-friendly clone of the classic platform game Super Mario Bros. In all, we compare the output of seven different level generators from the literature, based on different algorithmic methods, plus the levels from the original Super Mario Bros game. To compare them, we have de ned six expressivity metrics, of which two are novel contributions in this paper. These metrics are shown to provide interestingly di erent characterizations of the level generators. The results presented in this paper, and the accompanying source code, is meant to become a benchmark against which to test new level generators and expressivity metrics.

Place, publisher, year, edition, pages
Society for the Advancement of the Science of Digital Games , 2014. p. 1-8
Keywords [en]
Procedural Content Generation, Level Generators
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mau:diva-16786Local ID: 17062OAI: oai:DiVA.org:mau-16786DiVA, id: diva2:1420300
Conference
Foundations of Digital Games 2014, Ft. Lauderdale, Florida, USA (2014)
Available from: 2020-03-30 Created: 2020-03-30 Last updated: 2022-06-27Bibliographically approved
In thesis
1. Patterns and procedural content generation in digital games: automatic level generation for digital games using game design patterns
Open this publication in new window or tab >>Patterns and procedural content generation in digital games: automatic level generation for digital games using game design patterns
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The development of content in digital games, such as game worlds, quests, levels, 3D-models, and textures, is costly and time consuming. To address this, different approaches to automate the process of creating game content, often referred to as procedural content generation (PCG), has been suggested. However, PCG is a complex task and include challenges such as creating content with variation, coherent style, speed, and correctness. The research in the thesis is concerned with generating game content with the aid of game design patterns, both by establishing models and exploring different methods to generate actual game content for different games. The methods include implementations of evolutionary computation, i.e. a set of search-based approaches that searches for instances of game design patterns on different abstraction levels that make up Super Mario Bros. (SMB) levels and a learning algorithm implementation based on a model (n-grams) of patterns from the original SMB-game. The different generators were evaluated with metrics concerned with the expressive range of the generators and with user tests.

Place, publisher, year, edition, pages
Malmö university, Faculty of Technology and Society, 2016. p. 269
Series
Studies in Computer Science ; 2
Keywords
Procedural Content Generation, Search-based, Genetic Algorithms, Digital Games, Design Patterns
National Category
Engineering and Technology
Identifiers
urn:nbn:se:mau:diva-7775 (URN)20371 (Local ID)978-91-7104-684-0 (ISBN)978-91-7104-685-7 (ISBN)20371 (Archive number)20371 (OAI)
Public defence
2016-06-10, Niagara, NI:B0E15, Malmö, 13:00 (English)
Opponent
Available from: 2020-02-28 Created: 2020-02-28 Last updated: 2022-06-27Bibliographically approved

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fulltext(3524 kB)445 downloads
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Dahlskog, Steve

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