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Multiobjective Exploration of the StarCraft Map Space
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2010 (English)Conference paper (Refereed) Published
Abstract [en]

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 StarCraft 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

Place, publisher, year, edition, pages
Copenhagen: IEEE , 2010.
Keyword [en]
Real-time strategy games, RTS, procedural content generation, evolutionary multiobjective optimization
National Category
Computer Science
URN: urn:nbn:se:bth-7672DOI: 10.1109/ITW.2010.5593346Local ID: 978-1-4244-6295-7 OAI: diva2:835316
2010 IEEE Conference on Computational Intelligence and Games (CIG)
Available from: 2012-09-18 Created: 2010-12-27 Last updated: 2015-06-30Bibliographically approved

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