Miranda Jane Emery

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In this paper we present a new approach to plan understanding that explains observed actions in terms of domain knowledge. The process operates over hierarchical methods and utilizes an incremental form of data-driven abductive inference. We report experiments on problems from the Monroe corpus that demonstrate a basic ability to construct plausible(More)
In this paper we propose an IEEE 802.11 wireless LAN (WLAN) based location tracking system for indoor and outdoor environments. The system is implemented using the received signal strength indication (RSSI) measurements and training-data based estimation techniques. Methods for acquiring, filtering and interpreting wireless data are discussed with emphasis(More)
In this paper we present a computational approach to key aspects of understanding social interactions. First, we specify a class of problems – understanding fables – that require inference about agents’ mental states from their behavior. After this, we review earlier work on UMBRA, an abductive system for single-agent plan understanding, and describe(More)
The literature on problem solving in both humans and machines has revealed a diverse set of strategies that operate in different manners. In this paper, we review this great variety of techniques and propose a five-stage framework for problem solving that accounts for this variation in terms of differences in strategic knowledge used at each stage. We(More)
Humans exhibit the remarkable ability to solve complex, multi-step problems despite their limited capacity for search. We review the standard theory of problem solving, which posits that heuristic guidance makes this possible, but we also note that most studies have emphasized the role of domain-specific heuristics, which are not available for unfamiliar(More)
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