Regret-based utility elicitation in constraint-based decision problems

Authors:
Craig Boutilier;Relu Patrascu;Pascal Poupart;Dale Schuurmans
Affiliations:
Dept. of Computer Science, University of Toronto;Dept. of Computer Science, University of Toronto;School of Computer Science, University of Waterloo;Dept. of Computing Science, University of Alberta
Venue:
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Year:
2005

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Abstract

We propose new methods of preference elicitation for constraint-based optimization problems based on the use of minimax regret. Specifically, we assume a constraintbased optimization problem (e.g., product configuration) in which the objective function (e.g., consumer preferences) are unknown or imprecisely specified. Assuming a graphical utility model, we describe several elicitation strategies that require the user to answer only binary (bound) queries on the utility model parameters. While a theoretically motivated algorithm can provably reduce regret quickly (in terms of number of queries), we demonstrate that, in practice, heuristic strategies perform much better, and are able to find optimal (or near-optimal) configurations with far fewer queries.