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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 29 / No.1: The Twenty-Ninth Conference on Artificial Intelligence

Assessing the Robustness of Cremer-McLean with Automated Mechanism Design

March 8, 2023

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Authors

Michael Albert

The Ohio State University


Vincent Conitzer

Duke University


Giuseppe Lopomo

Duke University


DOI:

10.1609/aaai.v29i1.9293


Abstract:

In a classic result in the mechanism design literature, Cremerand McLean (1985) show that if buyers’ valuations are sufficiently correlated, a mechanism exists that allows the seller to extract the full surplus from efficient allocation as revenue. This result is commonly seen as “too good to be true” (in practice), casting doubt on its modeling assumptions. In this paper, we use an automated mechanism design approach to assess how sensitive the Cremer-McLean result is to relaxing its main technical assumption. That assumption implies that each valuation that a bidder can have results in a unique conditional distribution over the external signal(s). We relax this, allowing multiple valuations to be consistent with the same distribution over the external signal(s). Using similar insights to Cremer-McLean, we provide a highly efficient algorithm for computing the optimal revenue in this more general case. Using this algorithm, we observe that indeed, as the number of valuations consistent with a distribution grows, the optimal revenue quickly drops to that of a reserve-price mechanism. Thus, automated mechanism design allows us to gain insight into the precise sense in which Cremer-McLean is “too good to be true.”

Topics: AAAI

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HOW TO CITE:

Michael Albert|| Vincent Conitzer|| Giuseppe Lopomo Assessing the Robustness of Cremer-McLean with Automated Mechanism Design Proceedings of the AAAI Conference on Artificial Intelligence, 29 (2015) .

Michael Albert|| Vincent Conitzer|| Giuseppe Lopomo Assessing the Robustness of Cremer-McLean with Automated Mechanism Design AAAI 2015, .

Michael Albert|| Vincent Conitzer|| Giuseppe Lopomo (2015). Assessing the Robustness of Cremer-McLean with Automated Mechanism Design. Proceedings of the AAAI Conference on Artificial Intelligence, 29, .

Michael Albert|| Vincent Conitzer|| Giuseppe Lopomo. Assessing the Robustness of Cremer-McLean with Automated Mechanism Design. Proceedings of the AAAI Conference on Artificial Intelligence, 29 2015 p..

Michael Albert|| Vincent Conitzer|| Giuseppe Lopomo. 2015. Assessing the Robustness of Cremer-McLean with Automated Mechanism Design. "Proceedings of the AAAI Conference on Artificial Intelligence, 29". .

Michael Albert|| Vincent Conitzer|| Giuseppe Lopomo. (2015) "Assessing the Robustness of Cremer-McLean with Automated Mechanism Design", Proceedings of the AAAI Conference on Artificial Intelligence, 29, p.

Michael Albert|| Vincent Conitzer|| Giuseppe Lopomo, "Assessing the Robustness of Cremer-McLean with Automated Mechanism Design", AAAI, p., 2015.

Michael Albert|| Vincent Conitzer|| Giuseppe Lopomo. "Assessing the Robustness of Cremer-McLean with Automated Mechanism Design". Proceedings of the AAAI Conference on Artificial Intelligence, 29, 2015, p..

Michael Albert|| Vincent Conitzer|| Giuseppe Lopomo. "Assessing the Robustness of Cremer-McLean with Automated Mechanism Design". Proceedings of the AAAI Conference on Artificial Intelligence, 29, (2015): .

Michael Albert|| Vincent Conitzer|| Giuseppe Lopomo. Assessing the Robustness of Cremer-McLean with Automated Mechanism Design. AAAI[Internet]. 2015[cited 2023]; .


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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