Preventing Strategic Manipulation in Iterative Auctions: Proxy Agents and Price-Adjustment
Abstract
Iterative auctions have many computational advantages over sealed-bid auctions, but can present new possibilities for strategic manipulation. We propose a two-stage technique to make iterative auctions that compute optimal allocations with myopic best-response bidding strategies more robust to manipulation. First, introduce proxy bidding agents to con-strain bidding strategies to (possibly untruthful) myopic best-response. Second, after the auction terminates adjust the prices towards those given in the Vickrey auction, a sealed-bid auction in which truth-revelation is optimal. We present an application of this methodology to iBundle, an iterative combinatorial auction which gives optimal allocations for myopic best-response agents.
Cite
Text
Parkes and Ungar. "Preventing Strategic Manipulation in Iterative Auctions: Proxy Agents and Price-Adjustment." AAAI Conference on Artificial Intelligence, 2000.Markdown
[Parkes and Ungar. "Preventing Strategic Manipulation in Iterative Auctions: Proxy Agents and Price-Adjustment." AAAI Conference on Artificial Intelligence, 2000.](https://mlanthology.org/aaai/2000/parkes2000aaai-preventing/)BibTeX
@inproceedings{parkes2000aaai-preventing,
title = {{Preventing Strategic Manipulation in Iterative Auctions: Proxy Agents and Price-Adjustment}},
author = {Parkes, David C. and Ungar, Lyle H.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2000},
pages = {82-89},
url = {https://mlanthology.org/aaai/2000/parkes2000aaai-preventing/}
}