论文标题
对数符号分布的信号游戏:垃圾箱数量和平衡的属性
Signaling Games for Log-Concave Distributions: Number of Bins and Properties of Equilibria
论文作者
论文摘要
我们研究了真正的随机变量和二次成本标准的分散廉价谈话问题的平衡行为,其中编码器和解码器的目标函数错误。在先前的工作中,已经表明,由于克劳福德和索贝尔(Crawford)和索贝尔(Sobel),考虑到$ [0,1] $支持密度的来源,任何均衡中的垃圾箱数量都必须可计划,这是概括的经典结果。在本文中,我们首先在对数洞穴源的背景下完善此结果。对于具有双面无界支撑的来源,我们证明,对于任何有限数量的垃圾箱,都存在独特的平衡。相比之下,对于具有半空支持的来源,根据某些条件明确指定的条件,可能会有有限的上限在平衡中的垃圾箱数量。此外,我们证明,对于对数孔的源,编码器的预期成本和平衡的解码器随着箱数的增加而减小。此外,对于具有两侧无界支持的严格对数符号源,我们证明了最佳响应动力学在给定数量的垃圾箱开始,与劳埃德方法的最佳量化和融合结果的经典理论有关。此外,我们考虑了满足分布尾部某些假设的更多通用来源,并且我们表明,对于具有双面无界支持的来源,存在无限多个垃圾箱的平衡。为具有指数,高斯和紧凑型概率分布的来源提供了进一步的明确特征。
We investigate the equilibrium behavior for the decentralized cheap talk problem for real random variables and quadratic cost criteria in which an encoder and a decoder have misaligned objective functions. In prior work, it has been shown that the number of bins in any equilibrium has to be countable, generalizing a classical result due to Crawford and Sobel who considered sources with density supported on $[0,1]$. In this paper, we first refine this result in the context of log-concave sources. For sources with two-sided unbounded support, we prove that, for any finite number of bins, there exists a unique equilibrium. In contrast, for sources with semi-unbounded support, there may be a finite upper bound on the number of bins in equilibrium depending on certain conditions stated explicitly. Moreover, we prove that for log-concave sources, the expected costs of the encoder and the decoder in equilibrium decrease as the number of bins increases. Furthermore, for strictly log-concave sources with two-sided unbounded support, we prove convergence to the unique equilibrium under best response dynamics which starts with a given number of bins, making a connection with the classical theory of optimal quantization and convergence results of Lloyd's method. In addition, we consider more general sources which satisfy certain assumptions on the tail(s) of the distribution and we show that there exist equilibria with infinitely many bins for sources with two-sided unbounded support. Further explicit characterizations are provided for sources with exponential, Gaussian, and compactly-supported probability distributions.