Iterated Weaker-than-Weak Dominance
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 1233-1237.
Abstract
We introduce a weakening of standard game-theoretic dominance conditions, called δ-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, δ. We can apply elimination of δ-dominated strategies iteratively, but the δ 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.
@inproceedings{ijcai2007p199,
title = {Iterated Weaker-than-Weak Dominance},
author = {Cheng, Shih-Fen and Wellman, Michael P.},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {1233--1237},
year = {2007},
url = {https://ijcai.org/proceedings/2007/199},
}
TY - CPAPER TI - Iterated Weaker-than-Weak Dominance AU - Cheng, Shih-Fen AU - Wellman, Michael P. T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 1233 EP - 1237 UR - https://ijcai.org/proceedings/2007/199 ER -Copied
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