Mean field equilibria of dynamic auctions with learning: A dynamic revenue equivalence theorem

Krishnamurthy R Iyer; Ramesh Johari; Mukund Sundararajan

doi:10.1109/Allerton.2011.6120276

Mean field equilibria of dynamic auctions with learning: A dynamic revenue equivalence theorem

Krishnamurthy R Iyer, Ramesh Johari, Mukund Sundararajan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

Auctions are observed as a market mechanism in a wide range of economic transactions involving repeated interactions among the market participants: sponsored search markets run by Google and Yahoo!, online marketplaces such as eBay and Amazon, crowdsourcing, etc. In many of these markets, the participants typically have incomplete information; for example, the participants may not know the quality of the good being auctioned or their value for the good. In such settings, repeated interactions among the participants give rise to extremely complex bidder behavior due to the presence of learning among the participants.

Original language	English (US)
Title of host publication	2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011
Pages	1002-1003
Number of pages	2
DOIs	https://doi.org/10.1109/Allerton.2011.6120276
State	Published - 2011
Externally published	Yes
Event	2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011 - Monticello, IL, United States Duration: Sep 28 2011 → Sep 30 2011

Publication series

Name	2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011

Other

Other	2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011
Country/Territory	United States
City	Monticello, IL
Period	9/28/11 → 9/30/11

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10.1109/Allerton.2011.6120276

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Iyer, K. R., Johari, R., & Sundararajan, M. (2011). Mean field equilibria of dynamic auctions with learning: A dynamic revenue equivalence theorem. In 2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011 (pp. 1002-1003). Article 6120276 (2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011). https://doi.org/10.1109/Allerton.2011.6120276

Mean field equilibria of dynamic auctions with learning: A dynamic revenue equivalence theorem. / Iyer, Krishnamurthy R; Johari, Ramesh; Sundararajan, Mukund.
2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011. 2011. p. 1002-1003 6120276 (2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Iyer, KR, Johari, R & Sundararajan, M 2011, Mean field equilibria of dynamic auctions with learning: A dynamic revenue equivalence theorem. in 2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011., 6120276, 2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011, pp. 1002-1003, 2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011, Monticello, IL, United States, 9/28/11. https://doi.org/10.1109/Allerton.2011.6120276

Iyer KR, Johari R, Sundararajan M. Mean field equilibria of dynamic auctions with learning: A dynamic revenue equivalence theorem. In 2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011. 2011. p. 1002-1003. 6120276. (2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011). doi: 10.1109/Allerton.2011.6120276

Iyer, Krishnamurthy R ; Johari, Ramesh ; Sundararajan, Mukund. / Mean field equilibria of dynamic auctions with learning : A dynamic revenue equivalence theorem. 2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011. 2011. pp. 1002-1003 (2011 49th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2011).

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Mean field equilibria of dynamic auctions with learning: A dynamic revenue equivalence theorem

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