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All Outputs (5)

Evolving unipolar memristor spiking neural networks (2015)
Journal Article
Howard, G. D., Bull, L., & De Lacy Costello, B. (2015). Evolving unipolar memristor spiking neural networks. Connection Science, 27(4), 397-416. https://doi.org/10.1080/09540091.2015.1080225

© 2015 Taylor & Francis. Neuromorphic computing – brain-like computing in hardware – typically requires myriad complimentary metal oxide semiconductor spiking neurons interconnected by a dense mesh of nanoscale plastic synapses. Memristors are freq... Read More about Evolving unipolar memristor spiking neural networks.

A brief history of learning classifier systems: from CS-1 to XCS and its variants (2015)
Journal Article
Bull, L. (2015). A brief history of learning classifier systems: from CS-1 to XCS and its variants. Evolutionary Intelligence, 8(2-3), 55-70. https://doi.org/10.1007/s12065-015-0125-y

© 2015, Springer-Verlag Berlin Heidelberg. The direction set by Wilson’s XCS is that modern Learning Classifier Systems can be characterized by their use of rule accuracy as the utility metric for the search algorithm(s) discovering useful rules. Suc... Read More about A brief history of learning classifier systems: from CS-1 to XCS and its variants.

On the evolution of Boolean networks for computation: A guide RNA mechanism (2015)
Journal Article
Bull, L. (2016). On the evolution of Boolean networks for computation: A guide RNA mechanism. International Journal of Parallel, Emergent and Distributed Systems, 31(2), 101-113. https://doi.org/10.1080/17445760.2015.1057590

© 2015 Taylor & Francis. There is a growing body of work within computational intelligence which explores the use of representations inspired by the genetic regulatory networks of biological cells. This paper uses a recently presented abstract, tun... Read More about On the evolution of Boolean networks for computation: A guide RNA mechanism.

A Cognitive Architecture Based on a Learning Classifier System with Spiking Classifiers (2015)
Journal Article
Howard, D., Howard, G. D., Bull, L., & Lanzi, P. L. (2016). A Cognitive Architecture Based on a Learning Classifier System with Spiking Classifiers. Neural Processing Letters, 44(1), 125-147. https://doi.org/10.1007/s11063-015-9451-4

© 2015, Springer Science+Business Media New York. Learning classifier systems (LCS) are population-based reinforcement learners that were originally designed to model various cognitive phenomena. This paper presents an explicitly cognitive LCS by usi... Read More about A Cognitive Architecture Based on a Learning Classifier System with Spiking Classifiers.

On the evolution of behaviors through embodied imitation (2015)
Journal Article
Erbas, M. D., Bull, L., & Winfield, A. F. (2015). On the evolution of behaviors through embodied imitation. Artificial Life, 21(2), 141-165. https://doi.org/10.1162/ARTL_a_00164

© 2015 Massachusetts Institute of Technology. Abstract This article describes research in which embodied imitation and behavioral adaptation are investigated in collective robotics. We model social learning in artificial agents with real robots. The... Read More about On the evolution of behaviors through embodied imitation.