TITLE: Expressive but Solvable: Balancing Elicitation, Learning, and Reasoning to Construct a Personalized Scheduling Model

PRESENTER: Neil Yorke-Smith, http://www.ai.sri.com/~nysmith, nysmith@ai.sri.com

AFFILIATION:Artificial Intelligence Center, SRI International, http://www.ai.sri.com/

DATE: Friday 12th September 2008

TIME: 12:00:00

PLACE: CSE Seminar Room, Level 1, K17

ABSTRACT:

To have value for an individual who is arranging an event, a scheduling
tool must actively account for your scheduling preferences, especially
when the meeting request constraints 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 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.

BIOGRAPHY OF SPEAKER:

Neil Yorke-Smith is a Computer Scientist at SRI's Artificial
Intelligence Center. His research focuses on technologies that assist
human decision making, with interests including planning and scheduling,
preferences, constraint programming, advisable agents, and intelligent
user interfaces, and their real-world applications. He received his
Ph.D. from Imperial College London in 2004. Publications and further
information are available at: http://www.ai.sri.com/~nysmith

Host:

Toby Walsh

Seminar Convenor:

Van Hai Ho