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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 26 / No. 1: Twenty-Sixth AAAI Conference on Artificial Intelligence

Approximately Revenue-Maximizing Auctions for Deliberative Agents

March 8, 2023

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Authors

L. Celis

University of Washington


Anna Karlin

University of Washington


Kevin Leyton-Brown

University of British Columbia


C. Nguyen

Facebook


David Thompson

University of British Columbia


DOI:

10.1609/aaai.v26i1.8270


Abstract:

In many real-world auctions, a bidder does not know her exact value for an item, but can perform a costly deliberation to reduce her uncertainty. Relatively little is known about such deliberative environments, which are fundamentally different from classical auction environments. In this paper, we propose a new approach that allows us to leverage classical revenue-maximization results in deliberative environments. In particular, we use Myerson (1981) to construct the first non-trivial (i.e., dependent on deliberation costs) upper bound on revenue in deliberative auctions. This bound allows us to apply existing results in the classical environment to a deliberative environment. In addition, we show that in many deliberative environments the only optimal dominant-strategy mechanisms take the form of sequential posted-price auctions.

Topics: AAAI

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HOW TO CITE:

L. Celis|| Anna Karlin|| Kevin Leyton-Brown|| C. Nguyen|| David Thompson Approximately Revenue-Maximizing Auctions for Deliberative Agents Proceedings of the AAAI Conference on Artificial Intelligence, 26 (2012) 1313.

L. Celis|| Anna Karlin|| Kevin Leyton-Brown|| C. Nguyen|| David Thompson Approximately Revenue-Maximizing Auctions for Deliberative Agents AAAI 2012, 1313.

L. Celis|| Anna Karlin|| Kevin Leyton-Brown|| C. Nguyen|| David Thompson (2012). Approximately Revenue-Maximizing Auctions for Deliberative Agents. Proceedings of the AAAI Conference on Artificial Intelligence, 26, 1313.

L. Celis|| Anna Karlin|| Kevin Leyton-Brown|| C. Nguyen|| David Thompson. Approximately Revenue-Maximizing Auctions for Deliberative Agents. Proceedings of the AAAI Conference on Artificial Intelligence, 26 2012 p.1313.

L. Celis|| Anna Karlin|| Kevin Leyton-Brown|| C. Nguyen|| David Thompson. 2012. Approximately Revenue-Maximizing Auctions for Deliberative Agents. "Proceedings of the AAAI Conference on Artificial Intelligence, 26". 1313.

L. Celis|| Anna Karlin|| Kevin Leyton-Brown|| C. Nguyen|| David Thompson. (2012) "Approximately Revenue-Maximizing Auctions for Deliberative Agents", Proceedings of the AAAI Conference on Artificial Intelligence, 26, p.1313

L. Celis|| Anna Karlin|| Kevin Leyton-Brown|| C. Nguyen|| David Thompson, "Approximately Revenue-Maximizing Auctions for Deliberative Agents", AAAI, p.1313, 2012.

L. Celis|| Anna Karlin|| Kevin Leyton-Brown|| C. Nguyen|| David Thompson. "Approximately Revenue-Maximizing Auctions for Deliberative Agents". Proceedings of the AAAI Conference on Artificial Intelligence, 26, 2012, p.1313.

L. Celis|| Anna Karlin|| Kevin Leyton-Brown|| C. Nguyen|| David Thompson. "Approximately Revenue-Maximizing Auctions for Deliberative Agents". Proceedings of the AAAI Conference on Artificial Intelligence, 26, (2012): 1313.

L. Celis|| Anna Karlin|| Kevin Leyton-Brown|| C. Nguyen|| David Thompson. Approximately Revenue-Maximizing Auctions for Deliberative Agents. AAAI[Internet]. 2012[cited 2023]; 1313.


ISSN: 2374-3468


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