GeneRec

GeneRec is a generalization of the recirculation algorithm, and approximates Almeida-Pineda recurrent backpropagation.[1][2] It is used as part of the Leabra algorithm for error-driven learning.[3]

The symmetric, midpoint version of GeneRec is equivalent to the contrastive Hebbian learning algorithm (CHL).[1]

See also

References

  1. O'Reilly, R.C. Biologically Plausible Error-driven Learning using Local Activation Differences: The Generalized Recirculation Algorithm. Neural Computation, 8, 895-938. Abstract PDF
  2. GeneRec description in Computational explorations in cognitive neuroscience: understanding the mind by Randall C. O'Reilly, Yuko Munakata
  3. Leabra overview in Emergent


This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.