利用分离动力学从实验数据产生自组织集体行为
Generating self-organizing collective behavior using separation dynamics from experimental data
摘要：
已经提出了使用简单的局部规则的交互代理系统的数学模型，并显示出紧急群集行为。大多数这些模型是通过直觉或对真实现象的手动观察构建的，然后进行调整或验证以模拟所需的动态。与此相反，这种方法，我们建议使用一个模型，试图遵循一个平均规则的基本距离依赖的集体行为的真正的鸽子群，这是从实验数据中提取。通过使用一个简单的模型来跟踪真实数据的行为趋势，我们证明了我们的模型可以表现出涌现的自组织动力学，如群集，斑图形成和反向旋转的漩涡。我们的模拟中观察到的行为范围比集体动态的标准模型更丰富，因此应该为复杂行为的新模型提供潜力。
英文摘要：
Mathematical models for systems of interacting agents using simple local rules have been proposed and shown to exhibit emergent swarming behavior. Most of these models are constructed by intuition or manual observations of real phenomena, and later tuned or verified to simulate desired dynamics. In contrast to this approach, we propose using a model that attempts to follow an averaged rule of the essential distance-dependent collective behavior of real pigeon flocks, which was abstracted from experimental data. By using a simple model to follow the behavioral tendencies of real data, we show that our model can exhibit emergent self-organizing dynamics such as flocking, pattern formation, and counter-rotating vortices. The range of behaviors observed in our simulations are richer than the standard models of collective dynamics, and should thereby give potential for new models of complex behavior.
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