Memristor Hardware-Friendly Reinforcement Learning

no code implementations • 20 Jan 2020 • Nan Wu, Adrien Vincent, Dmitri Strukov, Yuan Xie

Namely, neuromorphic architectures that leverage memristors, the programmable and nonvolatile two-terminal devices, as synaptic weights in hardware neural networks, are candidates of choice to realize such highly energy-efficient and complex nervous systems.

reinforcement-learning Reinforcement Learning (RL)