Prior work has studied the computational complexity of computing optimal strategies to commit to in Stackelberg or leadership games, where a leader commits to a strategy which is observed by one or more followers. We extend this setting to one where the leader can additionally commit to outcome-conditional utility transfers. We characterize the computational complexity of finding optimal strategies in normal-form and Bayesian games, giving a mix of efficient algorithms and NP-hardness results. Finally, we allow the leader to also commit to a signaling scheme which induces a correlated equilibrium. In this setting, optimal commitments can be found in polynomial time for arbitrarily many players.

翻译：先前工作研究了在斯塔克尔伯格或领导力博弈中计算最优策略承诺的计算复杂度，其中领导者承诺一种策略，该策略被一个或多个跟随者观测。我们将这一设定扩展至领导者还可以承诺进行结果条件效用转移的场景。我们刻画了在正则形式和贝叶斯博弈中寻找最优策略的计算复杂度，给出了高效算法与NP难结论的混合结果。最后，我们允许领导者同时承诺一种诱导出相关均衡的信号方案。在此设定下，对于任意数量的参与者，最优承诺可以在多项式时间内求得。