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

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

See also

• Leabra
• O'Reilly (1996; Neural Computation)

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

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