Audit Games
Abstract
We focus on solving two-player zero-sum extensive-form games with perfect information and simultaneous moves. In these games, both players fully observe the current state of the game where they simultaneously make a move determining the next state of the game. We solve these games by a novel algorithm that relies on two components: (1) it iteratively solves the games that correspond to a single simultaneous move using a double-oracle method, and (2) it prunes the states of the game using bounds on the sub-game values obtained by the classical Alpha-Beta search on a serialized variant of the game. We experimentally evaluate our algorithm on the Goofspiel card game, a pursuit-evasion game, and randomly generated games. The results show that our novel algorithm typically provides significant running-time improvements and reduction in the number of evaluated nodes compared to the full search algorithm.
Cite
Text
Blocki et al. "Audit Games." International Joint Conference on Artificial Intelligence, 2013.Markdown
[Blocki et al. "Audit Games." International Joint Conference on Artificial Intelligence, 2013.](https://mlanthology.org/ijcai/2013/blocki2013ijcai-audit/)BibTeX
@inproceedings{blocki2013ijcai-audit,
title = {{Audit Games}},
author = {Blocki, Jeremiah and Christin, Nicolas and Datta, Anupam and Procaccia, Ariel D. and Sinha, Arunesh},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2013},
pages = {41-47},
url = {https://mlanthology.org/ijcai/2013/blocki2013ijcai-audit/}
}