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Using Case-Based Reasoning to Improve Real-Time Strategy Game AI

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dc.contributor.advisor Xu, Diana Barton, Daniel 2014-06-12T13:24:56Z 2014-06-12T13:24:56Z 2014
dc.description.abstract In recent years using real-time strategy (RTS) games as a test bed for Artificial Intelligence techniques has become increasingly popular. RTS games allow an environment that is complex enough to present the AI with a sufficiently challenging situation. These games also provide an easy way to evaluate the effectiveness of the technique. In this paper, I will describe how I built on the work of Aha, et al., who in [2] used a custom Case-Based Reasoner to govern an AI in Wargus, an open source RTS game, that learns to play better as it plays more games. I replicated their experiment with a different Case-Based Reasoner. I created and worked with BARC, a Case-Based Reasoner written in C++ for this specific application. BARC is based on the description of CAT in [2], but shares no source code.
dc.description.sponsorship Haverford College. Department of Computer Science
dc.language.iso eng
dc.subject.lcsh Games of strategy (Mathematics)
dc.subject.lcsh Artificial intelligence -- Computer programs
dc.title Using Case-Based Reasoning to Improve Real-Time Strategy Game AI
dc.type Thesis
dc.rights.access Open Access

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