Characteristics of Pattern Formation and Evolution in Approximations of Physarum Transport Networks
Characteristics of Pattern Formation and Evolution in Approximations of Physarum Transport Networks
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DOI：
10.1162/artl.2010.16.2.16202
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发表时间：
2010-03-01
期刊：
影响因子：
2.6
通讯作者：
Jones, Jeff
中科院分区：
文献类型：
--
作者：
Jones, Jeff
大多数模式形成的研究特别强调其在复杂的多细胞身体计划发展中的作用。然而，在更简单的生物体中，模式形成是生长和行为所固有的。受这样一种生物体，真正的黏液霉菌多头绒泡菌的启发，我们提出了复杂的紧急模式的形成和进化的例子，由一个简单的粒子状代理人的人口形成。利用基于趋化性的简单局部行为，移动的智能体群体自发地形成复杂的动态传输网络。通过调整简单的模型参数，得到特征图案图。参数映射的某些区域产生特别复杂的长期行为，包括网络空隙的循环收缩和网络路径的分叉以保持网络连通性。我们证明了不规则的斑点和网状图案的化学吸引力的形成。其他图灵样图案化方案是通过使用化学排斥行为获得的，包括规则的周期性斑点阵列和条纹图案的自组织。我们表明，复杂的模式类型可以产生不诉诸反应扩散机制的层次耦合。我们还提出了简单的预图案线索所产生的网络行为，给出了简单的例子，紧急模式形成过程如何演变成网络的功能和准物理特性，包括张力效应，网络最小化行为，并修复网络损坏。结果解释在自然系统中的生物模式形成的经典理论，我们提出的机制，紧急模式形成过程可用作空间表示的非常规计算的方法。
Most studies of pattern formation place particular emphasis on its role in the development of complex multicellular body plans. In simpler organisms, however, pattern formation is intrinsic to growth and behavior. Inspired by one such organism, the true slime mold Physarum polycephalum, we present examples of complex emergent pattern formation and evolution formed by a population of simple particle-like agents. Using simple local behaviors based on chemotaxis, the mobile agent population spontaneously forms complex and dynamic transport networks. By adjusting simple model parameters, maps of characteristic patterning are obtained. Certain areas of the parameter mapping yield particularly complex long term behaviors, including the circular contraction of network lacunae and bifurcation of network paths to maintain network connectivity. We demonstrate the formation of irregular spots and labyrinthine and reticulated patterns by chemoattraction. Other Turing-like patterning schemes were obtained by using chemorepulsion behaviors, including the self-organization of regular periodic arrays of spots, and striped patterns. We show that complex pattern types can be produced without resorting to the hierarchical coupling of reaction-diffusion mechanisms. We also present network behaviors arising from simple pre-patterning cues, giving simple examples of how the emergent pattern formation processes evolve into networks with functional and quasi-physical properties including tensionlike effects, network minimization behavior, and repair to network damage. The results are interpreted in relation to classical theories of biological pattern formation in natural systems, and we suggest mechanisms by which emergent pattern formation processes may be used as a method for spatially represented unconventional computation.