带分布式输入的一致与不一致级联控制
Control of Agreement and Disagreement Cascades with Distributed Inputs
AI总结：
本研究针对自主通信智能体的协同决策问题，采用带注意力参数动态反馈调制的非线性意见动力学模型，揭示了意见级联触发与集体决策的影响因素及注意力动力学的隐式阈值作用。
摘要：
对于一组自主通信的智能体而言，区分有意义输入与干扰，并针对该输入达成集体一致或不一致的能力，对实现协同目标至关重要。本文研究了意见形成级联如何响应分布式输入信号，在网络化决策者群体中传播。通过采用带有注意力参数动态反馈调制的非线性意见动力学模型，我们揭示了意见级联的触发以及集体决策本身如何同时取决于分布式输入，以及由网络图谱特性决定的节点一致与不一致中心性。我们进一步表明，注意力动力学引入了一个隐式阈值，可区分能触发级联的分布式输入与被当作干扰而被拒绝的输入。
英文摘要：
For a group of autonomous communicating agents, the ability to distinguish a meaningful input from disturbance, and come to collective agreement or disagreement in response to that input, is paramount for carrying out coordinated objectives. In this work we study how a cascade of opinion formation spreads through a group of networked decision-makers in response to a distributed input signal. Using a nonlinear opinion dynamics model with dynamic feedback modulation of an attention parameter, we show how the triggering of an opinion cascade and the collective decision itself depend on both the distributed input and the node agreement and disagreement centrality, determined by the spectral properties of the network graph. We further show how the attention dynamics introduce an implicit threshold that distinguishes between distributed inputs that trigger cascades and ones that are rejected as disturbance.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
