Stackelberg equilibria have become increasingly important as a solution concept in computational game theory, largely inspired by practical problems such as security settings. In practice, however, there is typically uncertainty regarding the model about the opponent. This paper is, to our knowledge, the first to investigate Stackelberg equilibria under uncertainty in extensive-form games, one of the broadest classes of game. We introduce robust Stackelberg equilibria, where the uncertainty is about the opponent's payoffs, as well as ones where the opponent has limited lookahead and the uncertainty is about the opponent's node evaluation function. We develop a new mixed-integer program for the deterministic limited-lookahead setting. We then extend the program to the robust setting for Stackelberg equilibrium under unlimited and under limited lookahead by the opponent. We show that for the specific case of interval uncertainty about the opponent's payoffs (or about the opponent's node evaluations in the case of limited lookahead), robust Stackelberg equilibria can be computed with a mixed-integer program that is of the same asymptotic size as that for the deterministic setting.

本文研究了扩展形式博弈中存在不确定性的Stackelberg均衡及其鲁棒性问题，分别引入了关于对手收益以及对手节点估值函数的不确定性条件，并提出了一种新的混合整数规划模型计算此类问题，证明可以在特定情况下准确可靠地计算出鲁棒Stackelberg均衡。

广义形式博弈中的鲁棒斯塔克伯格均衡及其在有限展望中的扩展