Sotelo-López S A, Santos M C, Raposo E P, Viswanathan G M, da Luz M G E
Departamento de Física, Universidade Federal do Paraná, 81531-980, Curitiba-PR, Brazil.
Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Sep;86(3 Pt 1):031133. doi: 10.1103/PhysRevE.86.031133. Epub 2012 Sep 24.
Intuitively, lower target densities and lower detection capabilities should demand more sophisticated search strategies for a random search reasonable outcome. In contrast, when targets are easily found, a simple Brownian random walk strategy is enough. But where is the threshold between these two scenarios and when is optimization really necessary? We address this considering the interplay between two essential scales in random search, the average distance between neighbor targets l(0) and the detection capability r(v). In the limit cases the ratio β=r(v)/l(0) suffices to characterize the problem. For low (high) β a superdiffusive behavior is (is not) crucial for the process optimization. However, there is a crossover range, which is a nontrivial function of r(v) and l(0), separating the two regimes. We analyze this intermediate region, common in nature, and discuss the often overlooked important trade between resources availability and the searcher location power. Our results highlight contexts where efficient random search is a key factor for survival, such as in animal foraging.
直观地说,较低的目标密度和较低的探测能力需要更复杂的搜索策略才能获得随机搜索的合理结果。相比之下,当目标很容易被找到时,简单的布朗随机游走策略就足够了。但是这两种情况之间的界限在哪里,什么时候真正需要优化呢?我们通过考虑随机搜索中两个基本尺度之间的相互作用来解决这个问题,即相邻目标之间的平均距离l(0)和探测能力r(v)。在极限情况下,比率β = r(v)/l(0)足以表征该问题。对于低(高)β,超扩散行为对于过程优化至关重要(不重要)。然而,存在一个交叉范围,它是r(v)和l(0)的一个非平凡函数,将这两种情况区分开来。我们分析了这个自然界中常见的中间区域,并讨论了资源可用性和搜索者定位能力之间经常被忽视的重要权衡。我们的结果突出了有效随机搜索是生存关键因素的背景,例如在动物觅食中。