Levy flights do not always optimize random blind search for sparse targets
Levy flights do not always optimize random blind search for sparse targets
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DOI：
10.1073/pnas.1320424111
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发表时间：
2014-02-25
影响因子：
11.1
通讯作者：
Metzler, Ralf
中科院分区：
文献类型：
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作者：
Palyulin, Vladimir V.;Chechkin, Aleksei V.;Metzler, Ralf
一般认为，基于无标度、Levy稳定跳跃长度分布（Levy飞行）的随机搜索过程优化了对稀疏目标的搜索。在这里，我们表明，这种流行的搜索优势是不那么普遍的比通常假设的。我们研究了效率的最低限度的搜索模型的基础上利维航班在没有和存在的外部漂移（水下电流，大气风，偏好的步行者由于以往的经验，或一般的偏见在一个抽象的搜索空间）基于两个不同的优化标准，最小的搜索时间和搜索可靠性（累积到达概率）。虽然利维航班原来是有效的搜索过程中，当目标是远离起点，或相对于起点的目标是上游，我们表明，对于密切的目标和下游目标定位定期布朗运动原来是有利的搜索策略。相反的索赔，利维飞行与临界指数α = 1是最佳的稀疏目标在不同的设置中的搜索，基于我们的优化参数的最佳的α可以在整个区间（1，2）的范围内，特别是包括布朗运动作为整体最有效的搜索策略。
It is generally believed that random search processes based on scale-free, Levy stable jump length distributions (Levy flights) optimize the search for sparse targets. Here we show that this popular search advantage is less universal than commonly assumed. We study the efficiency of a minimalist search model based on Levy flights in the absence and presence of an external drift (underwater current, atmospheric wind, a preference of the walker owing to prior experience, or a general bias in an abstract search space) based on two different optimization criteria with respect to minimal search time and search reliability (cumulative arrival probability). Although Levy flights turn out to be efficient search processes when the target is far from the starting point, or when relative to the starting point the target is upstream, we show that for close targets and for downstream target positioning regular Brownian motion turns out to be the advantageous search strategy. Contrary to claims that Levy flights with a critical exponent alpha = 1 are optimal for the search of sparse targets in different settings, based on our optimization parameters the optimal a may range in the entire interval (1, 2) and especially include Brownian motion as the overall most efficient search strategy.