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Using Stereotypes and Compactification of Observations to Improve Modeling of Other Agents

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Author
Denzinger, Jorg
Hamdan, Jasmine
Accessioned
2008-02-27T16:58:46Z
Available
2008-02-27T16:58:46Z
Computerscience
2004-05-04
Issued
2004-05-04
Subject
Computer Science
Type
unknown
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Abstract
This paper investigates improvements to modeling other agents based on observed situation-action pairs and the nearest-neighbor rule, which suffers when dealing with very few or very many observations. Stereotype models allow for good predictions of a modeled agent s behavior even after few observations. To handle any adverse effects of stereotyping, periodic reevaluation of the chosen stereotype and the potential to switch between different stereotypes aids in dealing with very similar, but not identical, stereotypes. Also, periodic reevaluation and the potential to switch from a chosen stereotype to the original observation based modeling method aids in dealing with agents that do not conform to any stereotype. Finally, compactification of observation keeps the application of the original modeling method efficient by reducing comparisons within the nearest neighbor rule. <BR><BR>Our experiments within the OLEMAS system show that stereotyping significantly improves cases where just using the original modeling performs poorly. In addition, reevaluation and switching fortify stereotyping against the potential risk of using an incorrect stereotype. In many cases, compactification both increases the efficiency of using observed situation-action pairs and improves predictions by filtering out misleading observation. At times however, this filtering comes at the cost of prediction accuracy by removing relevant observations.
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We are currently acquiring citations for the work deposited into this collection. We recognize the distribution rights of this item may have been assigned to another entity, other than the author(s) of the work.If you can provide the citation for this work or you think you own the distribution rights to this work please contact the Institutional Repository Administrator at digitize@ucalgary.ca
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University of Calgary
Faculty
Science
Doi
http://dx.doi.org/10.11575/PRISM/30583
Uri
http://hdl.handle.net/1880/45848
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