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Exploiting prior knowledge in Intelligent Assistants - Combining relational models with hierarchies Natarajan, Sriraam Tadepalli, Prasad Fern, Alan Statistical Relational Learning Intelligent Assistants Statitsical relational models have been successfully used to model static probabilistic relationships between the entities of the domain. In this talk, we illustrate their use in a dynamic decison-theoretic setting where the task is to assist a user by inferring his intentional structure and taking appropriate assistive actions. We show that the statistical relational models can be used to succintly express the system's prior knowledge about the user's goal-subgoal structure and tune it with experience. As the system is better able to predict the user's goals, it improves the effectiveness of its assistance. We show through experiments that both the hierarchical structure of the goals and the parameter sharing facilitated by relational models significantly improve the learning speed. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Sriraam Natarajan and Prasad Tadepalli and Alan Fern 2008 Is Part Of Dagstuhl Seminar Proceedings, Volume 7161, Probabilistic, Logical and Relational Learning - A Further Synthesis (2008) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagSemProc.07161.3 urn:nbn:de:0030-drops-13856 https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07161.3 eng https://creativecommons.org/licenses/by/4.0/legalcode