论文标题
定量游戏中的对手stackelberg价值
The Adversarial Stackelberg Value in Quantitative Games
论文作者
论文摘要
在本文中，我们研究了具有平均值和打折的和折扣的函数在双重加权图上播放的两人非零和游戏的对抗性stackelberg值的概念。玩家0的对抗性stackelberg值是玩家0在宣布策略1时可以获得的最大价值，而球员1又以他的最佳响应做出了响应。对于平均支付函数，我们表明，对抗性stackelberg的价值并不总是可以实现的，但是存在Epsilon-Primatimal的策略。我们展示了如何计算此值并证明关联的阈值问题在NP中。对于打折的总收入功能，我们绘制了一个带有目标折扣总和问题的链接，这说明了为什么难以解决该回报功能的问题。我们还提供有关相关差距问题的解决方案。
In this paper, we study the notion of adversarial Stackelberg value for two-player non-zero sum games played on bi-weighted graphs with the mean-payoff and the discounted sum functions. The adversarial Stackelberg value of Player 0 is the largest value that Player 0 can obtain when announcing her strategy to Player 1 which in turn responds with any of his best response. For the mean-payoff function, we show that the adversarial Stackelberg value is not always achievable but epsilon-optimal strategies exist. We show how to compute this value and prove that the associated threshold problem is in NP. For the discounted sum payoff function, we draw a link with the target discounted sum problem which explains why the problem is difficult to solve for this payoff function. We also provide solutions to related gap problems.
