Finite-time Analysis of the Multiarmed Bandit Problem
Machine Learning
Incentive compatible multi unit combinatorial auctions
Proceedings of the 9th conference on Theoretical aspects of rationality and knowledge
Truthful Mechanisms for One-Parameter Agents
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
Weak monotonicity suffices for truthfulness on convex domains
Proceedings of the 6th ACM conference on Electronic commerce
Truthful randomized mechanisms for combinatorial auctions
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Truthful mechanism design for multi-dimensional scheduling via cycle monotonicity
Proceedings of the 8th ACM conference on Electronic commerce
Mechanism Design via Differential Privacy
FOCS '07 Proceedings of the 48th Annual IEEE Symposium on Foundations of Computer Science
Truthful germs are contagious: a local to global characterization of truthfulness
Proceedings of the 9th ACM conference on Electronic commerce
Characterizing truthful multi-armed bandit mechanisms: extended abstract
Proceedings of the 10th ACM conference on Electronic commerce
The price of truthfulness for pay-per-click auctions
Proceedings of the 10th ACM conference on Electronic commerce
Truthful mechanisms with implicit payment computation
Proceedings of the 11th ACM conference on Electronic commerce
Multi-unit auctions: beyond roberts
Proceedings of the 12th ACM conference on Electronic commerce
A truthful mechanism for value-based scheduling in cloud computing
SAGT'11 Proceedings of the 4th international conference on Algorithmic game theory
Proceedings of the 13th ACM Conference on Electronic Commerce
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In this paper we show that payment computation essentially does not present any obstacle in designing truthful mechanisms, even for multi-parameter domains, and even when we can only call the allocation rule once. We present a general reduction that takes any allocation rule which satisfies "cyclic monotonicity" (a known necessary and sufficient condition for truthfulness) and converts it to a truthful mechanism using a single call to the allocation rule, with arbitrarily small loss to the expected social welfare. A prominent example for a multi-parameter setting in which an allocation rule can only be called once arises in sponsored search auctions. These are multi-parameter domains when each advertiser has multiple possible ads he may display, each with a different value per click. Moreover, the mechanism typically does not have complete knowledge of the click-realization or the click-through rates (CTRs); it can only call the allocation rule a single time and observe the click information for ads that were presented. On the negative side, we show that an allocation that is truthful for any realization essentially cannot depend on the bids, and hence cannot do better than random selection for one agent. We then consider a relaxed requirement of truthfulness, only in expectation over the CTRs. Even for that relaxed version, making any progress is challenging as standard techniques for construction of truthful mechanisms (as using VCG or an MIDR allocation rule) cannot be used in this setting. We design an allocation rule with non-trivial performance and directly prove it is cyclic-monotone, and thus it can be used to create a truthful mechanism using our general reduction.