Persuasion with Coarse Communication

Yunus C. Aybas, E. Turkel
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引用次数: 10

Abstract

Persuasion is an exceedingly difficult task. A leading cause of this difficulty is the misalignment of preferences, which is studied extensively by the literature on persuasion games. However, the difficulty of communication also has a first order effect on the outcomes and welfare of agents. Motivated by this observation, we study a model of Bayesian Persuasion in which the communication between the sender and the receiver is constrained. This is done by allowing the cardinality of the signal space to be less than the cardinality of the action space and the state space, which limits the number of action recommendations that the sender can make. Existence of a maximum to the sender's problem is proven and its properties are characterized. This generalizes the standard Bayesian Persuasion framework, in which existence results rely on the assumption of rich signal spaces. We analyze the sender's willingness to pay for an additional signal as a function of the prior belief, which can be interpreted as the value of precise communication. We provide an upper bound for this value which applies to all finite persuasion games. While increased precision is always better for the sender, we show that the receiver might prefer coarse communication. We show this by analyzing a game of advice seeking, where the receiver has the ability to choose the size of the signal space.
用粗糙的沟通说服
说服是一项极其困难的任务。造成这种困难的一个主要原因是偏好的错位,这在说服游戏的文献中得到了广泛的研究。然而,沟通困难对代理人的结果和福利也有一级影响。受此启发,我们研究了一个贝叶斯说服模型,在这个模型中,发送者和接收者之间的交流是受限的。这是通过允许信号空间的基数小于操作空间和状态空间的基数来实现的,这限制了发送方可以提出的操作建议的数量。证明了发送方问题的极大值的存在性,并对其性质进行了刻画。这推广了标准贝叶斯说服框架,其中存在性结果依赖于对丰富信号空间的假设。我们分析了发送者支付额外信号的意愿作为先验信念的函数,这可以解释为精确通信的价值。我们为这个值提供了一个上界,它适用于所有有限说服博弈。虽然提高精度对发送方总是更好,但我们表明接收方可能更喜欢粗糙的通信。我们通过分析一个寻求建议的游戏来证明这一点,在这个游戏中,接收者有能力选择信号空间的大小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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