Conference Proceeding Article
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.
Artificial Intelligence and Robotics | Operations Research, Systems Engineering and Industrial Engineering
Intelligent Systems and Decision Analytics
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence IJCAI-07: Hyderabad, India, 6-12 January, 2007
City or Country
Menlo Park, CA
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. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/840
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