Abstract
User models play a critical role in robust plan recognition by controlling ambiguity. They allow an observer to prefer one plan explanation over another, and they provide a means of measuring the believability of misconceptions when the user's plan is flawed. This paper discusses the motivation for including a user model in robust plan recognition, and shows how a probabilistic interpretation offers a practical means of incorporating a user model into the plan recognition process.
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Calistri-Yeh, R.J. Utilizing user models to handle ambiguity and misconceptions in robust plan recognition. User Model User-Adap Inter 1, 289–322 (1991). https://doi.org/10.1007/BF00141047
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DOI: https://doi.org/10.1007/BF00141047