The signals used in persuasion mechanisms in practice typically satisfy two well-studied simple properties: (i) they partition an ordered state space into intervals, and (ii) they do not recommend lower actions at higher states. These properties have been studied—often separately—in the Bayesian persuasion literature, where conditions for the optimality of such signals are provided in various settings.

The two properties can be defined only when the action and the state space are ordered. Under the proper ordering conditions, we show that the optimal signal features both of these properties, as well as robustness properties, when Receiver is a pessimist. A pessimistic receiver, rather than maximizing expected payoff, takes the action that guarantees the highest level of payoff. Through the notion of maxmin expected utility, our findings explain that simplicity and robustness of optimal signals can emerge from the ambiguity of the prior to Receiver.

在实践中，说服机制中使用的信号通常满足两个经过充分研究的简单属性：（i）它们将有序状态空间划分为间隔，以及（ii）它们不建议在较高状态下采取较低的行动。在贝叶斯说服文献中已经研究了这些特性——通常是单独研究的，其中在各种设置中提供了此类信号的最优条件。

只有当动作和状态空间有序时，才能定义这两个属性。在适当的排序条件下，我们表明，当 Receiver 是悲观主义者时，最佳信号具有这些特性和稳健性特性。悲观的接收者，而不是最大化预期收益，而是采取保证最高收益水平的行动。通过maxmin 期望效用的概念，我们的研究结果解释了最优信号的简单性和鲁棒性可以从接收器先验的模糊性中显现出来。