DagSemProc.07161.3.pdf
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Exploiting prior knowledge in Intelligent Assistants - Combining relational models with hierarchies
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Dagstuhl Seminar Proceedings, Volume 7161
Series: Dagstuhl Seminar Proceedings (DagSemProc) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2008-03-06
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Sriraam Natarajan, Prasad Tadepalli, and Alan Fern. Exploiting prior knowledge in Intelligent Assistants - Combining relational models with hierarchies. In Probabilistic, Logical and Relational Learning - A Further Synthesis. Dagstuhl Seminar Proceedings, Volume 7161, pp. 1-2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)
https://doi.org/10.4230/DagSemProc.07161.3
https://doi.org/10.4230/DagSemProc.07161.3
Abstract
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.
Keywords
- Statistical Relational Learning
- Intelligent Assistants
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