Optimization and Elicitation with the Maximin Utility Criterion
نویسندگان
چکیده
We investigate robust decision-making under utility uncertainty, using the maximin criterion, which optimizes utility for the worst case setting. We show how it is possible to efficiently compute the maximin optimal recommendation in face of utility uncertainty, even in large configuration spaces. We then introduce a new decision criterion, setwise maximin utility (SMMU), for constructing optimal recommendation sets: we develop algorithms for computing SMMU, and prove (analogously to previous results related to regret-based and Bayesian elicitation) that SMMU determines choice sets for queries that are myopically optimal. We also present experimental results showing performance of SMMU on randomly generated elicitation problems.
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Robust Optimization of Recommendation Sets with the Maximin Utility Criterion
We investigate robust decision-making under utility uncertainty, using the maximin criterion, which optimizes utility for the worst case setting. We show how it is possible to efficiently compute the maximin optimal recommendation in face of utility uncertainty, even in large configuration spaces. We then introduce a new decision criterion, setwise maximin utility (SMMU), for constructing optim...
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