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者博弈中计算最优策略承诺的计算复杂性，其中领导者承诺一个策略，该策略被一个或多个追随者观察到。我们将此设定扩展至领导者额外能够承诺结果条件效用转移的情形。我们刻画了在正则型和贝叶斯博弈中寻找最优策略的计算复杂性，给出了高效算法与NP难性结果的混合结论。最后，我们允许领导者同时承诺一种能够诱导关联均衡的信号方案。在此设定下，对于任意多个玩家，最优承诺可在多项式时间内求得。