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Journal Articles PLoS Computational Biology Year : 2018

Limits on reliable information flows through stochastic populations

Abstract

Biological systems can share and collectively process information to yield emergent effects, despite inherent noise in communication. While man-made systems often employ intricate structural solutions to overcome noise, the structure of many biological systems is more amorphous. It is not well understood how communication noise may affect the computational repertoire of such groups. To approach this question we consider the basic collective task of rumor spreading, in which information from few knowledgeable sources must reliably flow into the rest of the population. We study the effect of communication noise on the ability of groups that lack stable structures to efficiently solve this task. We present an impossibility result which strongly restricts reliable rumor spreading in such groups. Namely, we prove that, in the presence of even moderate levels of noise that affect all facets of the communication , no scheme can significantly outperform the trivial one in which agents have to wait until directly interacting with the sources-a process which requires linear time in the population size. Our results imply that in order to achieve efficient rumor spread a system must exhibit either some degree of structural stability or, alternatively, some facet of the communication which is immune to noise. We then corroborate this claim by providing new analyses of experimental data regarding recruitment in Cataglyphis niger desert ants. Finally, in light of our theoretical results, we discuss strategies to overcome noise in other biological systems.
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Dates and versions

hal-01953778 , version 1 (14-12-2018)
hal-01953778 , version 2 (19-07-2021)

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Lucas Boczkowski, Emanuele Natale, Ofer Feinerman, Amos Korman. Limits on reliable information flows through stochastic populations. PLoS Computational Biology, 2018, 14 (6), ⟨10.1371/journal.pcbi.1006195⟩. ⟨hal-01953778v2⟩
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