Date of Original Version
Copyright © 2015 International Joint Conferences on Artificial Intelligence
Abstract or Description
Limited lookahead has been studied for decades in perfect-information games. This paper initiates a new direction via two simultaneous deviation points: generalization to imperfect-information games and a game-theoretic approach. The question of how one should act when facing an opponent whose lookahead is limited is studied along multiple axes: lookahead depth, whether the opponent(s), too, have imperfect information, and how they break ties. We characterize the hardness of finding a Nash equilibrium or an optimal commitment strategy for either player, showing that in some of these variations the problem can be solved in polynomial time while in others it is PPADhard or NP-hard. We proceed to design algorithms for computing optimal commitment strategies for when the opponent breaks ties 1) favorably, 2) according to a fixed rule, or 3) adversarially. The impact of limited lookahead is then investigated experimentally. The limited-lookahead player often obtains the value of the game if she knows the expected values of nodes in the game tree for some equilibrium, but we prove this is not sufficient in general. Finally, we study the impact of noise in those estimates and different lookahead depths. This uncovers a lookahead pathology
Proceedings of the International Joint Conference on Artificial Intelligence, 2015, 575-581.