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Tuning positive feedback for signal detection in noisy dynamic environments
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Analysis and Applied Mathematics.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Analysis and Applied Mathematics.
2012 (English)In: Journal of Theoretical Biology, ISSN 0022-5193, E-ISSN 1095-8541, Vol. 309, 88-95 p.Article in journal (Refereed) Published
Abstract [en]

Learning from previous actions is a key feature of decision-making. Diverse biological systems, from neuronal assemblies to insect societies, use a combination of positive feedback and forgetting of stored memories to process and respond to input signals. Here we look how these systems deal with a dynamic two-armed bandit problem of detecting a very weak signal in the presence of a high degree of noise. We show that by tuning the form of positive feedback and the decay rate to appropriate values, a single tracking variable can effectively detect dynamic inputs even in the presence of a large degree of noise. In particular, we show that when tuned appropriately a simple positive feedback algorithm is Fisher efficient, in that it can track changes in a signal on a time of order L(h)= (vertical bar h vertical bar/sigma)(-2), where vertical bar h vertical bar is the magnitude of the signal and sigma the magnitude of the noise.

Place, publisher, year, edition, pages
2012. Vol. 309, 88-95 p.
Keyword [en]
Self-organisation, Ant foraging, Bandit problems, Biochemical systems
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:uu:diva-181389DOI: 10.1016/j.jtbi.2012.05.023ISI: 000307526200010OAI: oai:DiVA.org:uu-181389DiVA: diva2:557701
Available from: 2012-09-28 Created: 2012-09-24 Last updated: 2017-12-07Bibliographically approved

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Sumpter, David J. T.

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