dc.contributor.advisor | Aamodt, Agnar | nb_NO |
dc.contributor.author | Szczepanski, Tomasz Szymon | nb_NO |
dc.date.accessioned | 2014-12-19T13:36:53Z | |
dc.date.available | 2014-12-19T13:36:53Z | |
dc.date.created | 2011-02-01 | nb_NO |
dc.date.issued | 2010 | nb_NO |
dc.identifier | 393815 | nb_NO |
dc.identifier | ntnudaim:5559 | nb_NO |
dc.identifier.uri | http://hdl.handle.net/11250/252332 | |
dc.description.abstract | Real-time strategy (RTS) games are both popular among players as well as among academics. A typical RTS gameplay can be divided into macromanagement and micromanagement. Other researchers have successfully applied Case-based reasoning (CBR) and case-based planning techniques in RTS games. While several of those approaches have beaten random pools of static scripted computer opponents, only a few approaches are focusing on the micromanagement aspect of RTS games. Traces Based Reasoning (TBR) is an enhancement to the conventional CBR methodology that adds the use of user-system interaction logs (traces). We present a CBR system that we convert into a TBR system that is used for micromanagement in RTS games. We explore various ways of micromanagement representations as well as case retrieval mechanisms suited for a system using the TBR paradigm. We test the system against a dynamic opponent in a micromanagement setting to present some of the difficulties involved in such an approach. | nb_NO |
dc.language | eng | nb_NO |
dc.publisher | Institutt for datateknikk og informasjonsvitenskap | nb_NO |
dc.subject | ntnudaim:5559 | no_NO |
dc.subject | SIF2 datateknikk | no_NO |
dc.subject | Intelligente systemer | no_NO |
dc.title | Game AI: micromanagement in Star Craft. | nb_NO |
dc.type | Master thesis | nb_NO |
dc.source.pagenumber | 61 | nb_NO |
dc.contributor.department | Norges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskap | nb_NO |