Since the release of BWAPI in 2009, StarCraft has taken the position as the leading platform for research in artificial intelligence in real-time strategy games. With competitions being held annually at AIIDE and CIG, there is much prestige in having an agent compete and do well. This thesis is aimed at presenting a model for doing opponent modeling and strategic reasoning in StarCraft.We present a method for constructing a model based on strategies, on the form of build orders, learned from expert demonstrations. This model is aimed at recognizing the strategy of the opponent and selecting a strategy that is capable of countering the recognized strategy. The method puts weight on the ordering and timing of buildings in order to do advanced recognition.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ntnu-18449 |
Date | January 2012 |
Creators | Fjell, Magnus Sellereite, Møllersen, Stian Veum |
Publisher | Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, Institutt for datateknikk og informasjonsvitenskap |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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