Publication Details

A Preference Model for Over-Constrained Meeting Requests

by Berry, P. M. and Gervasio, M. and Peintner, B. and Yorke-Smith, N.

in Proceedings of AAAI 2007 Workshop on Preference Handling for Artificial Intelligence pp. 7–14,

Abstract

To have value for an individual tasked with arranging a meeting, a scheduling tool must actively account for the individual¢s scheduling preferences, especially when the meeting request must be relaxed. We develop a preference model designed to capture user scheduling preferences for overconstrained meeting requests between multiple people, and a methodology for preference elicitation to initially populate this model. The model is built around a 2-order Choquet integral representation. We explain a natural-language-based elicitation of the meeting request details and constraints, and outline the solving of the resulting constrained scheduling problem (with preferences). We then describe the display of solutions to the scheduling problem to the user, as candidate scheduling options with explanations, and detail unobtrusive learning of revisions to the preference model from the user¢s choices among the candidates. We report on initial assessment of the efficacy of such a preference model in terms of elicitation, learning, and reasoning.

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Associated Projects

Cognitive Assistant that Learns and Organizes As part of DARPA’s Personalized Assistant that Learns (PAL) program, SRI and team members are working on developing a next-generation "Cognitive Agent that Learns and Organizes" (CALO).

AIC Personnel

	Name	Title	E-mail
	Berry, Pauline M	Alumnus
	Gervasio, Melinda	Senior Computer Scientist
	Peintner, Bart	Sr. Computer Scientist
	Yorke-Smith, Neil	Computer Scientist