Denzinger, JörgHamdan, Jasmine Ali2005-08-162005-08-162004Hamdan, J. A. (2004). Improving modeling of other agents for behavior prediction using stereotypes and compactification of observations (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/235280612976505http://hdl.handle.net/1880/41570Bibliography: p. 176-186Some pages are in colour.This thesis presents two improvements to the Observed Situation-Action Pairs and the Nearest Neighbor Rule (OSAPs and NNR) modeling method. Reevaluative stereo­typing with switching deals with poor prediction accuracy resulting from modeling with few OSAPs by using a stereotype to model others, and incorporating periodic reevaluations and the ability to switch between stereotypes or to the basic modeling method to ensure the validity of a chosen stereotype and of the stereotyping process itself. Compactification of OSAPs through kd-tree structuring deals with poor modeling efficiency resulting from modeling with many OSAPs by structuring OSAPs according to a kd-tree and using a Pseudo-Approximate Nearest Neighbor search for modeling. Our experiments shows that using a correct stereotype improves modeling performance and reevaluations and switching prevent incorrect stereotypes from causing substantial damage, and that compactification can improve modeling efficiency - but may affect modeling performance.xiv, 186 leaves : ill. ; 30 cm.engUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.master thesis10.11575/PRISM/23528AC1 .T484 2004 H34