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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Biological Cyberneti...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Biological Cybernetics
Article . 1983 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
zbMATH Open
Article . 1983
Data sources: zbMATH Open
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Optimization of brownian search strategies

Optimization of Brownian search strategies
Authors: Hoffmann, Gerhard;

Optimization of brownian search strategies

Abstract

What are the simplest search strategies that lead an animal to a particular target, what are their limitations, and what changes can be made to develop more effective strategies? To answer these questions a class of search strategies was examined that require an animal to have only a minimal capacity for spatial orientation; the effectiveness of such strategies in solving the following basic search problem was determined. The animal begins its search at a distance r0 (starting distance) from a spatially fixed target. It detects the target when it has approached it to within a certain distance a (the detection radius). The analysed class of search strategies has the following characteristics: C1. The animal uses the same search strategy in all regions it enters. Therefore it needs no information as to the actual location of the target. C2. Its search strategy is constant in time. The animal has only to detect whether it has reached the target or not. C3. Once the animal has chosen a direction, it continues in that direction for a certain distance. This is the only way in which the preceding parts of the search affect the animal's decision as to the direction in which it will search next. In the long term the animal's movement directions are independent, with no preference for any particular direction. Despite their extreme simplicity in application these "Brownian" search strategies are remarkably successful (Fig. 1). Indeed, if the search is continued long enough the target is certain to be found. The success of the search depends in part on the search duration (Fig. 2) or the search-path length S, the starting distance and the detection radius. On the other hand, an animal can have a decisive influence on its degree of success simply by adjusting the frequency with which it changes its walking direction to match its sensory abilities. That is, a not-too-short Brownian search (S much greater than r0) is most successful when the searching animal, between the points at which it changes direction, walks approximately straight for a distance equal to the detection radius (Figs, 3 and 4). A further increase in search effectiveness is possible only by turning to another class of search strategies. These, however, demand that the animal either have more information about the position of its target at the beginning of the search or be able to organize its search behavior even over fairly long periods of time.

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Keywords

Behavior, Animal, Phthiraptera, Animals, Learning, Models, Psychological, optimization of Brownian search strategies, Animal behavior, Mathematics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
22
Average
Top 10%
Top 10%
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