Efficient search of multiple types of targets

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
Marina E WosniackM G E da Luz

Abstract

Random searches often take place in fragmented landscapes. Also, in many instances like animal foraging, significant benefits to the searcher arise from visits to a large diversity of patches with a well-balanced distribution of targets found. Up to date, such aspects have been widely ignored in the usual single-objective analysis of search efficiency, in which one seeks to maximize just the number of targets found per distance traversed. Here we address the problem of determining the best strategies for the random search when these multiple-objective factors play a key role in the process. We consider a figure of merit (efficiency function), which properly "scores" the mentioned tasks. By considering random walk searchers with a power-law asymptotic Lévy distribution of step lengths, p(ℓ)∼ℓ(-μ), with 1<μ≤3, we show that the standard optimal strategy with μ(opt)≈2 no longer holds universally. Instead, optimal searches with enhanced superdiffusivity emerge, including values as low as μ(opt)≈1.3 (i.e., tending to the ballistic limit). For the general theory of random search optimization, our findings emphasize the necessity to correctly characterize the multitude of aims in any concrete metric to compare among possible candidates...Continue Reading

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Citations

May 21, 2020·Journal of the Royal Society, Interface·Johannes NautaPieter Simoens
Oct 4, 2017·PLoS Computational Biology·Marina E WosniackMarcos G E da Luz
Feb 18, 2017·Physical Review. E·M ChupeauS Redner
Mar 22, 2021·Psychological Research·Marcos Bella-FernándezBeatriz Gil-Gómez de Liaño
Aug 7, 2021·Current Opinion in Behavioral Sciences·Dale ZhouDanielle S Bassett

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