From Local Growth to Global Optimization in Insect Built Networks

A. Perna, P. Kuntz, G. Theraulaz, C. Jost
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引用次数: 9

Abstract

Social insect colonies build large net-like systems: gallery and trail networks. Many such networks appear to show near-optimal performance. Focusing on the network system inside termite nests we address the question how simple agents with probabilistic behaviour can control and optimize the growth of a structure with size several magnitude orders above their perceptual range. We identify two major classes of mechanisms: (i) purely local mechanisms, which involve the arrangement of simple motifs according to predetermined rules of behaviour and (ii) local estimation of global quantities, where sizes, lengths, and numbers are estimated from densities, concentrations, and traffic. Theoretical considerations suggest that purely local mechanisms work better during early network formation and are less likely to fall into local optima. On the contrary, estimation of global properties is only possible on functional networks and is more likely to work through pruning. This latter mechanism may contribute to restore network functionalities following unpredicted changes of external conditions or network topology. An analysis of the network properties of Cubitermes termite nests supports the role of both classes of mechanisms, possibly in interplay with environmental conditions acting as a template. DOI: 10.4018/978-1-61350-092-7.ch007
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昆虫构建网络从局部增长到全局优化
群居昆虫群落建立了大型的网状系统:长廊和小径网络。许多这样的网络似乎表现出接近最佳的性能。聚焦于白蚁巢内的网络系统,我们解决了具有概率行为的简单代理如何控制和优化比其感知范围大几个数量级的结构的增长。我们确定了两大类机制:(i)纯局部机制,涉及根据预定的行为规则排列简单的图案;(ii)全局量的局部估计,其中大小、长度和数量是根据密度、浓度和流量估计的。理论考虑表明,纯局部机制在早期网络形成过程中工作得更好,并且不太可能陷入局部最优状态。相反,全局属性的估计只能在功能网络上实现,而且更有可能通过修剪来实现。后一种机制可能有助于在外部条件或网络拓扑发生不可预测的变化后恢复网络功能。对立方体白蚁巢穴的网络特性的分析支持这两类机制的作用,可能在与环境条件的相互作用中充当模板。DOI: 10.4018 / 978 - 1 - 61350 - 092 - 7. - ch007
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