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Hebbian Learning using Fixed Weight Evolved Dynamical 'Neural' Networks

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posted on 2023-06-07, 19:13 authored by Eduardo Izquierdo-Torres, Inman HarveyInman Harvey
We evolve small continuous-time recurrent neural networks with fixed weights that perform Hebbian learning behavior. We describe the performance of the best and smallest successful system, providing an in-depth analysis of its evolved mechanisms. Learning is shown to arise from the interaction between the multiple timescale dynamics. In particular, we show how the fast-time dynamics alter the slow-time dynamics, which in turn shapes the local behavior around the equilibrium points of the fast components by acting as a parameter to them.

History

Publication status

  • Published

Publisher

IEEE Press

Pages

8.0

Presentation Type

  • paper

Event name

Proceedings of the First IEEE Symposium on Artificial Life. (IEEE-ALife'07)

Event location

Hawaii

Event type

conference

ISBN

1-4244-0698-6

Department affiliated with

  • Informatics Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2012-02-06

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