Evolution and learning in neural networks: Dynamic correlation, relearning and thresholding

Carse, B. and Oreland, J. (2000) Evolution and learning in neural networks: Dynamic correlation, relearning and thresholding. Adaptive Behavior, 8 (3-4). pp. 297-312. ISSN 1059-7123

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Publisher's URL: http://dx.doi.org/10.1177/105971230000800305


Item Type:Article
Additional Information:An earlier version of this paper was originally presented at the Genetic and Evolutionary computational conference (GECCO) in July, 2000. The work explores the interactions between life-long learning and artificial evolution. The work is significant since it critically examines two existing theories of learning/evolution interaction and proposes a new mechanism by which this can occur; namely that lifetime learning can increase an individual's resilience to deleterious mutations during reproduction.
Uncontrolled Keywords:evolution, learning, neural networks, dynamic correlation, relearning, thresholding
Faculty/Department:Faculty of Environment and Technology
~Pre-2012 Faculty Structure > Faculty of Environment and Technology
~Pre-2010 Faculty Structure > Environment and Technology > Bristol Institute of Technology
ID Code:5889
Deposited By: R. Upload account
Deposited On:22 Jan 2010 15:10
Last Modified:22 Nov 2012 15:35

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