Sociogenesis in unbounded space: modelling self-organised cohesive collective motion
Sociogenesis in unbounded space: modelling self-organised cohesive collective motion
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DOI：
10.1088/1478-3975/acc4ff
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发表时间：
2023-05-01
期刊：
影响因子：
2
通讯作者：
Giuggioli，Luca
中科院分区：
文献类型：
--
作者：
Neu，Zohar;Giuggioli，Luca
在无界空间中保持随机移动的代理之间的凝聚力是许多需要分布式多代理系统的实际应用的基本功能。我们在1D无界空间中开发了一个生物启发的集体运动模型，以确保这种功能。使用内部代理的信念来估计系统的介观状态，代理运动耦合到一个动态自生成的社会排名变量。社会信息和个体运动之间的这种耦合被用来诱导空间自我排序，并产生一个自适应的、相对于群体的坐标系统，使无界空间中的随机运动稳定下来。我们调查的状态空间的模型的关键控制参数，并找到两个独立的制度，系统达到动态凝聚态，包括部分感知制度，系统自我选择最近的邻居的距离，以确保一个接近恒定的平均数的感应邻居。总的来说，我们的方法构成了集体运动模型的一个新的理论发展，因为它考虑了基于其社会环境的内部表征做出决策的代理人，这些内部表征明确考虑了动态内部变量的空间变化。
Maintaining cohesion between randomly moving agents in unbounded space is an essential functionality for many real-world applications requiring distributed multi-agent systems. We develop a bio-inspired collective movement model in 1D unbounded space to ensure such functionality. Using an internal agent belief to estimate the mesoscopic state of the system, agent motion is coupled to a dynamically self-generated social ranking variable. This coupling between social information and individual movement is exploited to induce spatial self-sorting and produces an adaptive, group-relative coordinate system that stabilises random motion in unbounded space. We investigate the state-space of the model in terms of its key control parameters and find two separate regimes for the system to attain dynamical cohesive states, including a Partial Sensing regime in which the system self-selects nearest-neighbour distances so as to ensure a near-constant mean number of sensed neighbours. Overall, our approach constitutes a novel theoretical development in models of collective movement, as it considers agents who make decisions based on internal representations of their social environment that explicitly take into account spatial variation in a dynamic internal variable.