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dc.contributor.authorSlinde, Anders Njøseng
dc.date.accessioned2012-08-28T08:34:00Z
dc.date.available2012-08-28T08:34:00Z
dc.date.issued2012-06-01eng
dc.date.submitted2012-06-01eng
dc.identifier.urihttp://hdl.handle.net/1956/5972
dc.description.abstractEmotions have been shown to play an important partin human decision making, and emotions inArtificial Intelligence have been shown to affectagent performance and believability. The aim ofthis thesis is to use EEG-data to model players'emotions. The emotion model was incorporated intothe existing Emotion module in the computer gameknown as StateCraft. Using artificial neuralnetworks as a tool, two different models of theplayers' emotions were created, a general modeland acountry specific model, resulting in fourdifferent configurations of the Emotion module.Simulationsof these four different configurations of theEmotion module were conducted.Statistical analysis of the simulation data showsthat the agents perform worse overall withemotionsthan without. The country specific model appearsto perform better than the general model in thesimulations. Analysis also indicates that the fournew EEG-based configurations perform worse overallthan the existing Emotion module which is based ongame states . The EEG-based emotions promote morerisky behavior, and for some countries that canhave a very negative effect on performance.en_US
dc.format.extent1561265 byteseng
dc.format.mimetypeapplication/pdfeng
dc.language.isoengeng
dc.publisherThe University of Bergeneng
dc.titleModeling emotions with EEG-data in StateCrafteng
dc.typeMaster thesisen_US
dc.description.localcodeINFO390
dc.description.localcodeMASV-INFO
dc.subject.nus735115eng
dc.subject.nsiVDP::Social science: 200::Media science and journalism: 310eng
fs.subjectcodeINFO390


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