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arXiv 1503.03261cs.ET
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黏菌模型中统计分析与估计的形态适应近似

Approximation of Statistical Analysis and Estimation by Morphological Adaptation in a Model of Slime Mould

Jeff Jones, Andrew Adamatzky

摘要:

真正的黏菌多头绒泡菌通过其原质运输网络的生长和适应来近似一系列复杂的计算,这激发了最近大量的研究,以了解这样一个简单的生物体如何能够执行如此复杂的壮举。由黏菌构建的网络的性质已知受到其环境中刺激的局部分布的影响。但是,黏菌的形态适应能提供关于其环境的整体统计特性的任何信息吗?我们探索这种可能性,使用基于颗粒的模型黏菌。我们演示了如何在虚拟黏菌的斑点形态适应可用作一个简单的计算机制,可以粗略地近似,imate统计分析,估计和跟踪。初步的结果包括近似的几何质心的2D形状,近似的算术平均值从空间表示的排序和未排序的数据分布,和估计和动态跟踪的运动物体的位置存在噪声污染的输入刺激。结果表明,有可能利用具有有限的个人计算能力的非常简单的组件的集体(例如,简单的机器人设备群),通过材料适应和感觉融合从复杂的数据集中提取统计特征。

英文摘要:

True slime mould Physarum polycephalum approximates a range of complex computations via growth and adaptation of its proto- plasmic transport network, stimulating a large body of recent research into how such a simple organism can perform such complex feats. The properties of networks constructed by slime mould are known to be in- fluenced by the local distribution of stimuli within its environment. But can the morphological adaptation of slime mould yield any information about the global statistical properties of its environment? We explore this possibility using a particle based model of slime mould. We demonstrate how morphological adaptation in blobs of virtual slime mould may be used as a simple computational mechanism that can coarsely approx- imate statistical analysis, estimation and tracking. Preliminary results include the approximation of the geometric centroid of 2D shapes, ap- proximation of arithmetic mean from spatially represented sorted and unsorted data distributions, and the estimation and dynamical tracking of moving object position in the presence of noise contaminated input stimuli. The results suggest that it is possible to utilise collectives of very simple components with limited individual computational ability (for ex- ample swarms of simple robotic devices) to extract statistical features from complex datasets by means of material adaptation and sensorial fusion.

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