Minimax Regret Methods for Decision Making with Imprecise Utility Functions
Craig Boutilier
(University of Toronto)
November 9th
Lubrano Conference Room

Abstract

Preference elicitation is generally required when making or recommending decisions on behalf of users whose utility function is not known with certainty. Although one can engage in elicitation until a utility function is perfectly known, in practice, this is infeasible. Thus methods for decision making with imprecise utility functions are needed. We propose the use of minimax regret as an appropriate decision criterion in this circumstance, providing the means for determining robust decisions. We overview recent techniques we have developed for minimax regret computation in several different settings, including constraint-based configuration, distributed resource allocation and (time permitting) mechanism design. We also describe how minimax regret can be used to drive the process of eliciting preferences itself.