A Cognitive Architecture Based on a Learning Classifier System with Spiking Classifiers

@article{Howard2015ACA,
  title={A Cognitive Architecture Based on a Learning Classifier System with Spiking Classifiers},
  author={Gerard David Howard and Larry Bull and Pier Luca Lanzi},
  journal={Neural Processing Letters},
  year={2015},
  volume={44},
  pages={125-147}
}
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 using spiking neural networks as classifiers, providing each classifier with a measure of temporal dynamism. We employ a constructivist model of growth of both neurons and synaptic connections, which permits a genetic algorithm to automatically evolve sufficiently-complex neural structures. The… 
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