Handling Uncertainty During Plan Recognition in Task-Oriented Consultation Systems

During interactions with human consultants, people are used to providing partial and/ or inaccurate information, and still be under­ stood and assisted. We attempt to em­ ulate this capability of human consultants in computer consultation systems. In this paper, we present a mechanism for han­ dling uncertainty in plan recognition dur­ ing task-oriented consultations. The uncer­ tainty arises while choosing an appropriate interpretation of a user's statements among many possible interpretations. Our mecha­ nism handles this uncertainty by using proba­ bility theory to assess the probabilities of the interpretations, and complements this assess­ ment by taking into account the information content of the interpretations. The informa­ tion content of an interpretation is a mea­ sure of how well defined an interpretation is in terms of the actions to be performed on the basis of the interpretation. This mea­ sure is used to guide the inference process to­ wards interpretations with a higher informa­ tion content. The information content of an interpretation depends on the specificity and the strength ofthe inferences in it, where the strength of an inference depends on the reli­ ability of the information on which the infer­ ence is based. Our mechanism has been de­ veloped for use in task-oriented consultation systems. The domain that we have chosen for exploration is that of a travel agency.