Constrained Automated Mechanism Design for Infinite Games of Incomplete Information
Abstract
We present a functional framework for automated Bayesian and worst-case mechanism design, based on a two-stage game model of strategic interaction between the designer and the mechanism participants. At the core of our framework is a black-box optimization algorithm which guides the process of evaluating candidate mechanisms. We apply the approach to several classes of two-player infinite games of incomplete information, producing optimal or nearly optimal mechanisms using various objective functions. By comparing our results with known optimal mechanisms, and in some cases improving on the best known mechanisms, we provide evidence that ours is a promising approach to parametrized mechanism design for infinite Bayesian games.
Cite
Text
Vorobeychik et al. "Constrained Automated Mechanism Design for Infinite Games of Incomplete Information." Conference on Uncertainty in Artificial Intelligence, 2007. doi:10.1007/s10458-011-9177-2Markdown
[Vorobeychik et al. "Constrained Automated Mechanism Design for Infinite Games of Incomplete Information." Conference on Uncertainty in Artificial Intelligence, 2007.](https://mlanthology.org/uai/2007/vorobeychik2007uai-constrained/) doi:10.1007/s10458-011-9177-2BibTeX
@inproceedings{vorobeychik2007uai-constrained,
title = {{Constrained Automated Mechanism Design for Infinite Games of Incomplete Information}},
author = {Vorobeychik, Yevgeniy and Reeves, Daniel M. and Wellman, Michael P.},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2007},
pages = {400-407},
doi = {10.1007/s10458-011-9177-2},
url = {https://mlanthology.org/uai/2007/vorobeychik2007uai-constrained/}
}