Gelblum Aviram, Pinkoviezky Itai, Fonio Ehud, Ghosh Abhijit, Gov Nir, Feinerman Ofer
Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 7610001, Israel.
Department of Chemical Physics, Weizmann Institute of Science, Rehovot 7610001, Israel.
Nat Commun. 2015 Jul 28;6:7729. doi: 10.1038/ncomms8729.
To cooperatively transport a large load, it is important that carriers conform in their efforts and align their forces. A downside of behavioural conformism is that it may decrease the group's responsiveness to external information. Combining experiment and theory, we show how ants optimize collective transport. On the single-ant scale, optimization stems from decision rules that balance individuality and compliance. Macroscopically, these rules poise the system at the transition between random walk and ballistic motion where the collective response to the steering of a single informed ant is maximized. We relate this peak in response to the divergence of susceptibility at a phase transition. Our theoretical models predict that the ant-load system can be transitioned through the critical point of this mesoscopic system by varying its size; we present experiments supporting these predictions. Our findings show that efficient group-level processes can arise from transient amplification of individual-based knowledge.
为了协同搬运重物,载体之间相互配合、齐心协力至关重要。行为从众的一个缺点是,它可能会降低群体对外部信息的反应能力。我们结合实验与理论,展示了蚂蚁如何优化集体运输。在单只蚂蚁层面,优化源于平衡个性与顺从的决策规则。从宏观层面来看,这些规则使系统处于随机游走和弹道运动之间的过渡状态,在此状态下,对一只获得信息的蚂蚁的引导,集体反应达到最大化。我们将这种反应峰值与相变时的磁化率发散联系起来。我们的理论模型预测,通过改变蚂蚁负载系统的大小,可以使其通过这个介观系统的临界点;我们展示了支持这些预测的实验。我们的研究结果表明,高效的群体层面过程可能源于基于个体的知识的短暂放大。