论文标题
具有可调灵敏度的非线性意见动力学
Nonlinear Opinion Dynamics with Tunable Sensitivity
论文作者
论文摘要
我们提出了经典线性加权平均意见动力学的连续时间多选非线性概括。与现有的线性和非线性模型相比，通过饱和的意见交流来引入非线性，这足以使我们的模型具有明显更大的舆论形成行为。对于通过网络传达观点的一组代理人，这些行为包括多样性的共识和分歧，对输入的可调节性敏感性，对干扰的鲁棒性，观点模式之间的灵活过渡以及意见级联。我们得出了与网络相关的调整规则来鲁棒控制系统行为，并为模型参数设计了状态反馈动力学，以使行为适应不断变化的外部条件。}模型为自然和工程网络的系统动态进行系统研究提供了新的手段，从信息传播和政治偏光到集体决策和动态任务分配和动态任务分配。
We propose a continuous-time multi-option nonlinear generalization of classical linear weighted-average opinion dynamics. Nonlinearity is introduced by saturating opinion exchanges, and this is enough to enable a significantly greater range of opinion-forming behaviors with our model as compared to existing linear and nonlinear models. For a group of agents that communicate opinions over a network, these behaviors include multistable agreement and disagreement, tunable sensitivity to input, robustness to disturbance, flexible transition between patterns of opinions, and opinion cascades. We derive network-dependent tuning rules to robustly control the system behavior and we design state-feedback dynamics for the model parameters to make the behavior adaptive to changing external conditions.} The model provides new means for systematic study of dynamics on natural and engineered networks, from information spread and political polarization to collective decision making and dynamic task allocation.
