Abstract
Improvement in the performance of reminder systems may be facilitated by the use of new representations. A decision-theoretic representation, for example, may enable a reminder system to represent and reason about the probabilities that a reminder will be a true or a false alarm and the relative utilities of these events. We extended a previously described decision-theoretic model to include such events. The model now represents explicitly the uncertainty, costs, and benefits of sending a reminder. We also extended the model to remove an assumption of reminder independence. As a step towards testing a hypothesis that this approach will support better performance than a rule-based approach, we analyzed a set of CARE rules and showed that our representation can represent these rules.
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Selected References
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