dc.contributor.advisor | Langseth, Helge | nb_NO |
dc.contributor.advisor | Kofod-Petersen, Anders | nb_NO |
dc.contributor.author | Fjell, Magnus Sellereite | nb_NO |
dc.contributor.author | Møllersen, Stian Veum | nb_NO |
dc.date.accessioned | 2014-12-19T13:38:52Z | |
dc.date.available | 2014-12-19T13:38:52Z | |
dc.date.created | 2012-11-08 | nb_NO |
dc.date.issued | 2012 | nb_NO |
dc.identifier | 565941 | nb_NO |
dc.identifier | ntnudaim:7163 | nb_NO |
dc.identifier.uri | http://hdl.handle.net/11250/252930 | |
dc.description.abstract | 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. | nb_NO |
dc.language | eng | nb_NO |
dc.publisher | Institutt for datateknikk og informasjonsvitenskap | nb_NO |
dc.subject | ntnudaim:7163 | no_NO |
dc.subject | MTDT datateknikk | no_NO |
dc.subject | Intelligente systemer | no_NO |
dc.title | Opponent Modeling and Strategic Reasoning in the Real-time Strategy Game Starcraft | nb_NO |
dc.type | Master thesis | nb_NO |
dc.source.pagenumber | 97 | nb_NO |
dc.contributor.department | Norges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskap | nb_NO |