Learning from Mistakes

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dc.creatorChialvo, Dante R.
dc.creatorBak, Per
dc.date1997-07-28
dc.date.accessioned2026-07-07T09:05:37Z
dc.date.available2026-07-07T09:05:37Z
dc.descriptionA simple model of self-organised learning with no classical (Hebbian) reinforcement is presented. Synaptic connections involved in mistakes are depressed. The model operates at a highly adaptive, probably critical, state reached by extremal dynamics similar to that of recent evolution models. Thus, one might think of the mechanism as synaptic Darwinism.
dc.description12 pages, Latex2e
dc.identifierhttps://arxiv.org/abs/adap-org/9707006
dc.identifierhttp://arxiv.org/abs/adap-org/9707006
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/149734
dc.subjectAdaptation and Self-Organizing Systems
dc.subjectCondensed Matter
dc.subjectQuantitative Biology
dc.titleLearning from Mistakes
dc.typetext

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