• Corpus ID: 238857279

Sign and Relevance learning

  title={Sign and Relevance learning},
  author={Sama Daryanavard and Bernd Porr},
Standard models of biologically realistic, or inspired, reinforcement learning employ a global error signal which implies shallow networks. However, deep networks could offer a drastically superior performance by feeding the error signal backwards through such a network which in turn is not biologically realistic as it requires symmetric weights between top-down and bottom-up pathways. Instead, we present a network combining local learning with global modulation where neuromodulation controls… 


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Is backpropagation biologically plausible?
  • D. Stork
  • Biology
    International 1989 Joint Conference on Neural Networks
  • 1989
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