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A two-step algorithm for learning from unspecific reinforcement

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We study a simple learning model based on the Hebb rule to cope with `delayed', unspecific reinforcement. In spite of the unspecific nature of the information-feedback, convergence to asymptotically perfect generalization is observed, with a rate depending, however, in a non-universal way on le...

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Main Authors: Kühn, Reimer (Author) , Stamatescu, Ion-Olimpiu (Author)
Format: Article (Journal)
Language:English
Published: 1999
In: Journal of physics. A, Mathematical and theoretical
Year: 1999, Volume: 32, Issue: 31
ISSN:1751-8121
DOI:10.1088/0305-4470/32/31/301
Online Access:Verlag, Volltext: http://dx.doi.org/10.1088/0305-4470/32/31/301
Verlag, Volltext: http://stacks.iop.org/0305-4470/32/i=31/a=301
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Author Notes:Reimer Kühn and Ion-Olimpiu Stamatescu
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A two step algorithm for learning from unspecific reinforcement by Kühn, Reimer (Author) , Stamatescu, Ion-Olimpiu (Author) ,


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