Towards evolving spiking networks with memristive synapses

Howard, G. D., Gale, E., Bull, L., de Lacy Costello, B. and Adamatzky, A. (2011) Towards evolving spiking networks with memristive synapses. In: IEEE Symopium on Artificial Life (ALIFE) 2011, Paris, France, 11th - 14th April, 2011. US: Institute of Electrical and Electronics Engineers ( IEEE ) , pp. 14-21 Available from:

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This paper presents a spiking neuro-evolutionary system which implements memristors as neuromodulatory connections, ie whose weights can vary during a trial. The evolutionary design process exploits parameter self-adaptation and a constructionist approach, allowing the number of neurons, connection weights, and inter-neural connectivity pattern to be evolved for each network. We demonstrate that this approach allows the evolution of networks of appropriate complexity to emerge whilst exploiting the ...

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:evolving spiking networks, memristive synapses, Hebbian theory, robot sensing systems, neurons, topology, mathematical model, genetic algorithms
Faculty/Department:Faculty of Environment and Technology > Department of Computer Science and Creative Technologies
ID Code:20713
Deposited By: M. Clarke
Deposited On:17 Jul 2013 09:25
Last Modified:12 Apr 2016 12:20

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