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Comparison of ant-inspired gatherer allocation approaches using memristor-based environmental models (2011)
Presentation / Conference
Gale, E., de Lacy Costello, B., & Adamatzky, A. (2011, December). Comparison of ant-inspired gatherer allocation approaches using memristor-based environmental models. Paper presented at Bioadcom 2011 Workshop on Bio-inspired Approaches to Advanced Computing and Communications (BioAdcom2011)

Memristors are used to compare three gathering techniques in an already-mapped environment where resource locations are known. The All Site model, which apportions gatherers based on the modeled memristance of that path, proves to be good at increasi... Read More about Comparison of ant-inspired gatherer allocation approaches using memristor-based environmental models.

Neuromorphic computing with memristors: Preliminary experimental results (2011)
Presentation / Conference
Gale, E., de Lacy Costello, B., & Adamatzky, A. (2011, November). Neuromorphic computing with memristors: Preliminary experimental results. Poster presented at Building Bridges to Build Brains

Individual memristors have been observed demonstrating neuron-like spiking patterns. It has been shown elsewhere that memristors provide superior modelling for neurons then the Hodgkin-Huxley model. Due to these results we expect memristors to be e... Read More about Neuromorphic computing with memristors: Preliminary experimental results.

Evolving spiking networks with variable memristors (2011)
Presentation / Conference
Howard, G. D., Gale, E., Bull, L., de Lacy Costello, B., & Adamatzky, A. (2011, June). Evolving spiking networks with variable memristors. Paper presented at 13th annual conference on Genetic and evolutionary computation

Towards evolving spiking networks with memristive synapses (2011)
Presentation / Conference
Howard, G. D., Gale, E., Bull, L., de Lacy Costello, B., & Adamatzky, A. (2011, April). Towards evolving spiking networks with memristive synapses. Paper presented at IEEE Symposium on Artificial Life (ALIFE), 2011

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 app... Read More about Towards evolving spiking networks with memristive synapses.


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