Self-Confirming Price Prediction Strategies for Simultaneous One-Shot Auctions

Michael P. Wellman, Eric Sodomka, Amy Greenwald
Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence, PMLR R10:892-901, 2012.

Abstract

Bidding in simultaneous auctions is challenging because an agent’s value for a good in one auction may depend on the uncertain outcome of other auctions: the so-called exposure problem. Given the gap in understanding of general simultaneous auction games, previous works have tackled this problem with heuristic strategies that employ probabilistic price predictions. We define a concept of self-confirming prices, and show that within an independent private value model, Bayes-Nash equilibrium can be fully characterized as a profile of optimal price prediction strategies with self-confirming predictions. We exhibit practical procedures to compute approximately optimal bids given a probabilistic price prediction, and near self-confirming price predictions given a price-prediction strategy. An extensive empirical game-theoretic analysis demonstrates that self-confirming price prediction strategies are effective in simultaneous auction games with both complementary and substitutable preference structures.

Cite this Paper

BibTeX
@InProceedings{pmlr-vR10-wellman12a, title = {Self-Confirming Price Prediction Strategies for Simultaneous One-Shot Auctions}, author = {Wellman, Michael P. and Sodomka, Eric and Greenwald, Amy}, booktitle = {Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence}, pages = {892--901}, year = {2012}, editor = {de Freitas, Nando and Murphy, Kevin}, volume = {R10}, series = {Proceedings of Machine Learning Research}, month = {14--18 Aug}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/r10/main/assets/wellman12a/wellman12a.pdf}, url = {https://proceedings.mlr.press/r10/wellman12a.html}, abstract = {Bidding in simultaneous auctions is challenging because an agent’s value for a good in one auction may depend on the uncertain outcome of other auctions: the so-called exposure problem. Given the gap in understanding of general simultaneous auction games, previous works have tackled this problem with heuristic strategies that employ probabilistic price predictions. We define a concept of self-confirming prices, and show that within an independent private value model, Bayes-Nash equilibrium can be fully characterized as a profile of optimal price prediction strategies with self-confirming predictions. We exhibit practical procedures to compute approximately optimal bids given a probabilistic price prediction, and near self-confirming price predictions given a price-prediction strategy. An extensive empirical game-theoretic analysis demonstrates that self-confirming price prediction strategies are effective in simultaneous auction games with both complementary and substitutable preference structures.}, note = {Reissued by PMLR on 04 October 2026.} }
Endnote
%0 Conference Paper %T Self-Confirming Price Prediction Strategies for Simultaneous One-Shot Auctions %A Michael P. Wellman %A Eric Sodomka %A Amy Greenwald %B Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence %C Proceedings of Machine Learning Research %D 2012 %E Nando de Freitas %E Kevin Murphy %F pmlr-vR10-wellman12a %I PMLR %P 892--901 %U https://proceedings.mlr.press/r10/wellman12a.html %V R10 %X Bidding in simultaneous auctions is challenging because an agent’s value for a good in one auction may depend on the uncertain outcome of other auctions: the so-called exposure problem. Given the gap in understanding of general simultaneous auction games, previous works have tackled this problem with heuristic strategies that employ probabilistic price predictions. We define a concept of self-confirming prices, and show that within an independent private value model, Bayes-Nash equilibrium can be fully characterized as a profile of optimal price prediction strategies with self-confirming predictions. We exhibit practical procedures to compute approximately optimal bids given a probabilistic price prediction, and near self-confirming price predictions given a price-prediction strategy. An extensive empirical game-theoretic analysis demonstrates that self-confirming price prediction strategies are effective in simultaneous auction games with both complementary and substitutable preference structures. %Z Reissued by PMLR on 04 October 2026.
APA
Wellman, M.P., Sodomka, E. & Greenwald, A.. (2012). Self-Confirming Price Prediction Strategies for Simultaneous One-Shot Auctions. Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence, in Proceedings of Machine Learning Research R10:892-901 Available from https://proceedings.mlr.press/r10/wellman12a.html. Reissued by PMLR on 04 October 2026.

Related Material