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A self-organizing model for task allocation via frequent task quitting and random walks in the honeybee

机译:通过频繁退出任务和蜜蜂随机游走的自组织模型,用于任务分配

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Social insect colonies are able to quickly redistribute their thousands of workers between tasks that vary strongly in space and time. How individuals collectively track spatial variability is particularly puzzling because bees have access only to local information. This work presents and tests a model showing how honeybees solve their fundamental within-nest spatial task-allocation problem. The algorithm, which is self-organizing and derived from empirical studies, couples two processes with opposing effects. Frequent task quitting, followed by patrols, during which bees are insensitive to task stimuli, serves to randomize individual location throughout the nest without reference to variation in task demand, while a foraging-for-work-like mechanism provides the opposing force of localizing individuals to areas of high task demand. This simple model is shown to generate sophisticated patterns of task allocation. It allocates bees to tasks in proportion to their demand, independent of their spatial distribution in the nest, and also reallocates labor in response to temporal changes in task demand. Finally, the model shows that task-allocation patterns at the colony level do not reflect colonies allocating particular individuals to tasks. In contrast, they reflect a dynamic equilibrium of workers switching between tasks and locations in the nest.
机译:社会昆虫群落能够在时空变化很大的任务之间迅速重新分配其成千上万的工人。人们如何集体跟踪空间变异性尤其令人困惑,因为蜜蜂只能访问本地信息。这项工作提出并测试了一个模型,该模型显示了蜜蜂如何解决其基本的巢内空间任务分配问题。该算法是自组织的,是根据经验研究得出的,将两个具有相反作用的过程耦合在一起。频繁的任务退出,然后进行巡逻,在此期间蜜蜂对任务的刺激不敏感,可在不考虑任务需求变化的情况下使整个巢内的个体位置随机化,而类似工作的觅食机制则提供了将个体定位的反作用力到高任务需求的区域。该简单模型显示出可以生成复杂的任务分配模式。它根据任务的需求将蜜蜂分配给任务,而不受其在巢中的空间分布的影响,还根据任务需求的时间变化重新分配劳动力。最后,该模型显示,菌落级别的任务分配模式不能反映出将特定个体分配给任务的菌落。相反,它们反映了工人在巢中的任务和位置之间切换的动态平衡。

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