A Reduced Spiking Neural Network Architecture for Energy Efficient Context-Dependent Reinforcement Learning Tasks
Hira Rasheed, Peyman Mirtaheri, Ali Muhtaroğlu
Neuromorphic circuits and systems involving spiking neural networks (SNN) have resulted in disruptive advances in performance/joule for relevant applications. A novel reinforcement learning (RL) digital hardware architecture is presented in this work that achieves energy consumption improvements through three fundamental techniques: The …
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