Adaptive Bayesian stimulus selection for enhanced learning in individuals

dc.contributor.advisornot available
dc.contributor.authorWildhagen, A.P.C.D.
dc.description.abstractPsychometric models have been used to parametrize a relevant model capturing the behavioral response of the user in a yes/no or 2AFC task. The obtained model would be analyzed in order to evaluate the performance of the user. Here I suggest a simple method to extend the psychometric curve to determine properties to enhance learning in tasks where it has been shown that learning takes place. We will look at the amount of trials needed in order to obtain the same results as Sa el & Matthews (2002) and see that in a simulated environment this method will produce the same results in a more e cient way.en_US
dc.embargo.typePermanent embargoen_US
dc.thesis.facultyFaculteit der Sociale Wetenschappenen_US
dc.thesis.specialisationBachelor Artificial Intelligenceen_US
dc.thesis.studyprogrammeArtificial Intelligenceen_US
dc.titleAdaptive Bayesian stimulus selection for enhanced learning in individualsen_US
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