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Knightian Robustness from Regret Minimization (1403.6409v2)

Published 25 Mar 2014 in cs.GT

Abstract: We consider auctions in which the players have very limited knowledge about their own valuations. Specifically, the only information that a Knightian player $i$ has about the profile of true valuations, $\theta*$, consists of a set of distributions, from one of which $\theta_i*$ has been drawn. We analyze the social-welfare performance of the VCG mechanism, for unrestricted combinatorial auctions, when Knightian players that either (a) choose a regret-minimizing strategy, or (b) resort to regret minimization only to refine further their own sets of undominated strategies, if needed. We prove that this performance is very good.

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