A two step algorithm for learning from unspecific reinforcement

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...

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Bibliographic Details
Main Authors: Kühn, Reimer (Author) , Stamatescu, Ion-Olimpiu (Author)
Format: Article (Journal) Chapter/Article
Language:English
Published: 1999
In: Arxiv

Online Access:Verlag, kostenfrei, Volltext: http://arxiv.org/abs/cond-mat/9902354
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Author Notes:Reimer Kühn, 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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