Swapna Reddy

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This paper describes a challenging plan recognition problem that arises in environments in which agents engage widely in exploratory behavior, and presents new algorithms for effective plan recognition in such settings. In exploratory domains, agents’ actions map onto logs of behavior that include switching between activities, extraneous actions, and(More)
Ideally designed software allow users to explore and pursue interleaving plans, making it challenging to automatically recognize user interactions. The recognition algorithms presented use constraint satisfaction techniques to compare user interaction histories to a set of ideal solutions. We evaluate these algorithms on data obtained from user interactions(More)
BACKGROUND Although program evaluation is a core requirement of Internal Medicine residencies, little is reported in the literature regarding resident satisfaction with training. Most program evaluation consists of numerical rating scales from which it is often difficult to pinpoint exact sources of dissatisfaction. METHODS Our goal in this work is to(More)
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