A self-adaptive hardware with resistive switching synapses for experience-based neurocomputing

Abstract

A big challenge for artificial intelligence is to gain the ability of learning by experience like biological systems. Here Bianchi et al. propose a hardware neural network based on resistive-switching synaptic arrays which dynamically adapt to the environment for autonomous exploration.