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Amoeba-based computing for traveling salesman problem: Long-term correlations between spatially separated individual cells of Physarum polycephalum

机译:基于Amoeba的旅行推销员问题计算:多头草的空间分隔单个细胞之间的长期相关性

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摘要

A single-celled, multi-nucleated amoeboid organism, a plasmodium of the true slime mold Physarum polycephalum, can perform sophisticated computing by exhibiting complex spatiotemporal oscillatory dynamics while deforming its amorphous body. We previously devised an " amoeba-based computer (ABC)" to quantitatively evaluate the optimization capability of the amoeboid organism in searching for a solution to the traveling salesman problem (TSP) under optical feedback control. In ABC, the organism changes its shape to find a high quality solution (a relatively shorter TSP route) by alternately expanding and contracting its pseudopod-like branches that exhibit local photoavoidance behavior. The quality of the solution serves as a measure of the optimality of which the organism maximizes its global body area (nutrient absorption) while minimizing the risk of being illuminated (exposure to aversive stimuli). ABC found a high quality solution for the 8-city TSP with a high probability. However, it remains unclear whether intracellular communication among the branches of the organism is essential for computing. In this study, we conducted a series of control experiments using two individual cells (two single-celled organisms) to perform parallel searches in the absence of intercellular communication. We found that ABC drastically lost its ability to find a solution when it used two independent individuals. However, interestingly, when two individuals were prepared by dividing one individual, they found a solution for a few tens of minutes. That is, the two divided individuals remained correlated even though they were spatially separated. These results suggest the presence of a long-term memory in the intrinsic dynamics of this organism and its significance in performing sophisticated computing.
机译:单细胞,多核变形虫生物(真正的粘液霉多头Phys)的疟原虫可以通过展现复杂的时空振荡动力学同时使其非晶形变形而执行复杂的计算。我们先前设计了一种“基于变形虫的计算机(ABC)”,以定量评估变形虫生物在光学反馈控制下寻找旅行商问题(TSP)的解决方案的优化能力。在ABC中,有机体通过交替扩展和收缩显示局部光回避行为的伪足状分支来改变其形状,从而找到高质量的溶液(相对较短的TSP路线)。解决方案的质量可作为衡量生物体最佳状态的一种指标,该生物体可最大化其整体身体区域(营养吸收),同时最大程度地降低被照亮的风险(接触厌恶性刺激)。美国广播公司极有可能为8城市TSP找到高质量的解决方案。但是,尚不清楚生物的分支之间的细胞内通讯是否对计算至关重要。在这项研究中,我们进行了一系列对照实验,使用两个单独的细胞(两个单细胞生物)在没有细胞间通讯的情况下进行平行搜索。我们发现,当ABC使用两个独立的人时,它彻底失去了寻找解决方案的能力。但是,有趣的是,当通过将一个人分开来准备两个人时,他们发现了几十分钟的解决方案。即,即使两个分开​​的个体在空间上是分开的,它们仍然保持相关。这些结果表明该生物体的内在动力学中存在长期记忆,并且在执行复杂的计算中具有重要意义。

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