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摘要翻译：
基于定性自然主义行为的模拟，已经提出了几种群体模型。在本文中，我们首次直接应用计算建模方法从实验数据推断植绒行为。我们表明，这种方法能够推断出群体成员之间或更一般地说，任何社区成员之间相互作用或缺乏相互作用的一般规则。通过对飞行中的信鸽的野外实验测量，我们证明了基本距离依赖的吸引/排斥关系的存在，并表明这一规律足以解释自然界中观察到的集体行为。个体随时间变化的位置数据被用作计算算法的输入数据，该算法能够构建复杂的非线性函数来表示系统的行为。拓扑最近邻相互作用被考虑来表征该模型中的组件。通过对经典（二维）Vicsek模型产生的噪声数据进行仿真，验证了该方法的有效性。应用于信鸽飞行的实验数据表明，更复杂的三维模型能够预测和模拟飞行轨迹，并显示出真实的集体动力学。通过对重构模型的仿真，提取了鸽子集体行为的特征，以及改变系统初始条件对鸽子集体行为的影响。我们的结果表明，这种方法可以应用于建立模型，能够模拟轨迹和集体动力学的实验测量牛群的运动。从这些模型中，可以推断出个体（动物）的行为。
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英文标题：
《Dynamical modeling of collective behavior from pigeon flight data: flock
cohesion and dispersion》
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作者：
Graciano Dieck Kattas, Xiao-Ke Xu and Michael Small
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最新提交年份：
2011
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分类信息：
一级分类：Quantitative Biology 数量生物学
二级分类：Other Quantitative Biology 其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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一级分类：Physics 物理学
二级分类：Biological Physics 生物物理学
分类描述：Molecular biophysics, cellular biophysics, neurological biophysics, membrane biophysics, single-molecule biophysics, ecological biophysics, quantum phenomena in biological systems (quantum biophysics), theoretical biophysics, molecular dynamics/modeling and simulation, game theory, biomechanics, bioinformatics, microorganisms, virology, evolution, biophysical methods.
分子生物物理、细胞生物物理、神经生物物理、膜生物物理、单分子生物物理、生态生物物理、生物系统中的量子现象（量子生物物理）、理论生物物理、分子动力学/建模与模拟、博弈论、生物力学、生物信息学、微生物、病毒学、进化论、生物物理方法。
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英文摘要：
Several models of flocking have been promoted based on simulations with qualitatively naturalistic behavior. In this paper we provide the first direct application of computational modeling methods to infer flocking behavior from experimental field data. We show that this approach is able to infer general rules for interaction, or lack of interaction, among members of a flock or, more generally, any community. Using experimental field measurements of homing pigeons in flight we demonstrate the existence of a basic distance dependent attraction/repulsion relationship and show that this rule is sufficient to explain collective behavior observed in nature. Positional data of individuals over time are used as input data to a computational algorithm capable of building complex nonlinear functions that can represent the system behavior. Topological nearest neighbor interactions are considered to characterize the components within this model. The efficacy of this method is demonstrated with simulated noisy data generated from the classical (two dimensional) Vicsek model. When applied to experimental data from homing pigeon flights we show that the more complex three dimensional models are capable of predicting and simulating trajectories, as well as exhibiting realistic collective dynamics. The simulations of the reconstructed models are used to extract properties of the collective behavior in pigeons, and how it is affected by changing the initial conditions of the system. Our results demonstrate that this approach may be applied to construct models capable of simulating trajectories and collective dynamics using experimental field measurements of herd movement. From these models, the behavior of the individual agents (animals) may be inferred.
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PDF链接：
https://arxiv.org/pdf/1110.1739
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