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

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dc.contributor.advisor Xu, Diana
dc.contributor.author Barton, Daniel
dc.date.accessioned 2014-06-12T13:24:56Z
dc.date.available 2014-06-12T13:24:56Z
dc.date.issued 2014
dc.identifier.uri http://hdl.handle.net/10066/14089
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.rights.uri http://creativecommons.org/licenses/by-nc/3.0/us/
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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http://creativecommons.org/licenses/by-nc/3.0/us/ Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by-nc/3.0/us/

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