Crowdsourced Bayesian auctions
Proceedings of the 3rd Innovations in Theoretical Computer Science Conference
Prior-free auctions with ordered bidders
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Near-optimal multi-unit auctions with ordered bidders
Proceedings of the fourteenth ACM conference on Electronic commerce
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In settings of incomplete information, we put forward (1) a very conservative-- indeed, purely set-theoretic --model of the beliefs (including totally wrong ones) that each player may have about the payoff types of his opponents, and (2) a new and robust solution concept, based on mutual belief of rationality, capable of leveraging such conservative beliefs. We exemplify the applicability of our new approach for single-good auctions, by showing that, under our solution concept, a normal-form, simple, and deterministic mechanism guarantees-- up to an arbitrarily small, additive constant --a revenue benchmark that is always greater than or equal to the second-highest valuation, and sometimes much greater. By contrast, we also prove that the same benchmark cannot even be approximated within any positive factor, under classical solution concepts.