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Limits on reliable information flows through stochastic populations

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 under...

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Published in:PLoS computational biology 2018-06, Vol.14 (6), p.e1006195
Main Authors: Boczkowski, Lucas, Natale, Emanuele, Feinerman, Ofer, Korman, Amos
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description 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.
doi_str_mv 10.1371/journal.pcbi.1006195
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subjects Algorithms
Animals
Ants
Behavior
Biology and Life Sciences
Communication
Computational biology
Computational Biology - methods
Computer and Information Sciences
Computer applications
Computer Science
Data processing
Deserts
Distributed processing
Distributed, Parallel, and Cluster Computing
Ecology and Environmental Sciences
Food
Formicidae
Information dissemination
Information processing
Models, Biological
Noise
Physiology
Population number
Population studies
Reproducibility of Results
Social Sciences
Spreading
Stochastic Processes
Stochasticity
Structural stability
Technology application
title Limits on reliable information flows through stochastic populations
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