Spiking AGREL
نویسندگان
چکیده
Spiking neural networks are characterised by the spiking neuron models they use and how these spiking neurons process information communicated through spikes – the neural code. We demonstrate a plausible spiking neural network based on Spike Response Models and predictive spike-coding. When combined with a plausible reinforcement learning strategy – Attention Gated REinforcement Learning (AGREL), we show that such predictive spiking neural networks can compute non-linear mappings, including XOR. Our spiking AGREL achieves similar performance as standard AGREL, with much more efficient neural coding.
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