Dynamics of Interacting Neural Networks

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dc.creatorKinzel, W.
dc.creatorMetzler, R.
dc.creatorKanter, I.
dc.date1999-06-04
dc.date2000-03-03
dc.date.accessioned2026-07-07T03:13:37Z
dc.date.available2026-07-07T03:13:37Z
dc.descriptionThe dynamics of interacting perceptrons is solved analytically. For a directed flow of information the system runs into a state which has a higher symmetry than the topology of the model. A symmetry breaking phase transition is found with increasing learning rate. In addition it is shown that a system of interacting perceptrons which is trained on the history of its minority decisions develops a good strategy for the problem of adaptive competition known as the Bar Problem or Minority Game.
dc.description9 pages, 3 figures; typos corrected, content reorganized
dc.identifierhttps://arxiv.org/abs/cond-mat/9906058
dc.identifierhttp://arxiv.org/abs/cond-mat/9906058
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/29366
dc.subjectDisordered Systems and Neural Networks
dc.titleDynamics of Interacting Neural Networks
dc.typetext

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