Hu Feng, Yang Fang
College of Physics and Electronic Engineering, Chongqing Normal University, Chongqing 400047, China.
College of Physics and Electronic Engineering, Chongqing Normal University, Chongqing 400047, China.
Biosystems. 2016 Mar;141:40-4. doi: 10.1016/j.biosystems.2016.02.001. Epub 2016 Feb 10.
We explore the dynamics of information propagation at the critical state of a biologically inspired system by an individual-based computer model. "Quorum response", a type of social interaction which has been recognized taxonomically in animal groups, is applied as the sole interaction rule among individuals. In the model, we assume a truncated Gaussian distribution to depict the distribution of the individuals' vigilance level. Each individual can assume either a naïve state or an alarmed one and only switches from the former state to the latter one. If an individual has turned into an alarmed state, it stays in the state during the process of information propagation. Initially, each individual is set to be at the naïve state and information is tapped into the system by perturbing an individual at the boundaries (alerting it to the alarmed state). The system evolves as individuals turn into the alarmed state, according to the quorum response rules, consecutively. We find that by fine-tuning the parameters of the mean and the standard deviation of the Gaussian distribution, the system is poised at a critical state. We present the phase diagrams to exhibit that the parameter space is divided into a super-critical and a sub-critical zone, in which the dynamics of information propagation varies largely. We then investigate the effects of the individuals' mobility on the critical state, and allow a proportion of randomly chosen individuals to exchange their positions at each time step. We find that mobility breaks down criticality of the system.
我们通过基于个体的计算机模型，探索了一个受生物启发的系统在临界状态下信息传播的动态过程。“群体响应”是一种在动物群体中已被分类识别的社会互动类型，被用作个体之间唯一的互动规则。在该模型中，我们假设截断高斯分布来描述个体警惕水平的分布。每个个体可以处于天真状态或警觉状态，且仅从前一种状态转变为后一种状态。如果一个个体转变为警觉状态，那么在信息传播过程中它将保持该状态。最初，每个个体都被设置为天真状态，通过在边界处扰动一个个体（使其转变为警觉状态）将信息引入系统。系统随着个体根据群体响应规则依次转变为警觉状态而演化。我们发现，通过微调高斯分布均值和标准差的参数，系统处于临界状态。我们给出相图以展示参数空间被划分为超临界区和亚临界区，其中信息传播的动态过程差异很大。然后我们研究个体移动性对临界状态的影响，并允许一定比例随机选择的个体在每个时间步交换位置。我们发现移动性破坏了系统的临界性。
