Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
1-2007
Abstract
We introduce a weakening of standard gametheoretic δ-dominance conditions, called dominance, which enables more aggressive pruning of candidate strategies at the cost of solution accuracy. Equilibria of a game obtained by eliminating a δ-dominated strategy are guaranteed to be approximate equilibria of the original game, with degree of approximation bounded by the dominance parameter. We can apply elimination of δ-dominated strategies iteratively, but the for which a strategy may be eliminated depends on prior eliminations. We discuss implications of this order independence, and propose greedy heuristics for determining a sequence of eliminations to reduce the game as far as possible while keeping down costs. A case study analysis of an empirical 2-player game serves to illustrate the technique, and demonstrate the utility of weaker-than-weak dominance pruning.
Discipline
Artificial Intelligence and Robotics | Operations Research, Systems Engineering and Industrial Engineering
Publication
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence IJCAI-07: Hyderabad, India, 6-12 January, 2007
First Page
1233
Last Page
1238
ISBN
9781577352983
Publisher
AAAI Press
City or Country
Menlo Park, CA
Citation
CHENG, Shih-Fen and WELLMAN, Michael P..
Iterated Weaker-than-Weak Dominance. (2007). Proceedings of the Twentieth International Joint Conference on Artificial Intelligence IJCAI-07: Hyderabad, India, 6-12 January, 2007. 1233-1238.
Available at: https://ink.library.smu.edu.sg/sis_research/840
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://www.aaai.org/Library/IJCAI/2007/ijcai07-199.php
Included in
Artificial Intelligence and Robotics Commons, Operations Research, Systems Engineering and Industrial Engineering Commons