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/}
}