Predicting human behavior in smart environments: theory and application to gaze prediction Mohammed, Redwan Abdo Abdullah , 1979- (VerfasserIn) Staadt, Oliver , 1968- (GutachterIn) Kirste, Thomas , 1962- (GutachterIn) Sprekeler, Henning , 1976- (GutachterIn) Schwabe, Lars , 1974- (GutachterIn) Universität Rostock (Grad verleihende Institution) Universität Rostock Fakultät für Informatik und Elektrotechnik (Grad verleihende Institution) Text theses Text Hochschulschrift 2015 2015 eng electronic resourceremoteComputermedienOnline-Ressource1 Online-Ressource Predicting human behavior is desirable in many application scenarios in smart environments. The existing models for eye movements do not take contextual factors into account. This addressed in this thesis using a systematic machine-learning approach, where user profiles for eye movements behaviors are learned from data. In addition, a theoretical innovation is presented, which goes beyond pure data analysis. The thesis proposed the modeling of eye movements as a Markov Decision Processes. It uses Inverse Reinforcement Learning paradigm to infer the user eye movements behaviors.<eng> submitted by M. Sc. Redwan Abdo Abdullah Mohammed from Rostock Dissertation Universität Rostock 2016 004 ST 300 54.72 http://rosdok.uni-rostock.de/resolve/urn/urn:nbn:de:gbv:28-diss2017-0029-6 Predicting human behavior in smart environments--(DE-627)88079559X urn:nbn:de:gbv:28-diss2017-0029-6 oclc: 974781320 ppn: (DE-627)881598240