Carse, B. and Oreland, J.
Evolution and learning in neural networks: Dynamic correlation, relearning and thresholding.
Adaptive Behavior, 8 (3-4).
Available from: http://eprints.uwe.ac.uk/5889
Full text not available from this repository
Publisher's URL: http://dx.doi.org/10.1177/105971230000800305
|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|
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|Deposited On:||22 Jan 2010 15:10|
|Last Modified:||10 Apr 2016 09:34|
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