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We consider the problem of multi-robot taskallocation when robots have to deal with uncertain utility estimates. Typically an allocation is performed to maximize expected utility; we consider a means for measuring the robustness of a given optimal allocation when robots have some measure of the uncertainty (e.g., a probability distribution, or moments of such distributions). We introduce a new O(n 4 ) algorithm, the Interval Hungarian algorithm, that extends the classic Kuhn-Munkres Hungariandoi:10.1177/0278364911404579 fatcat:3zhpdddegzejhm4kjmdqbgk2pu