Acting successfully in dynamic environments requires learning supported by two systems that differ in computational demand: a fast, model-free system that repeats rewarded actions, and a more ...
Model-free optical processors using in situ reinforcement learning with proximal policy optimization
Optical computing holds promise for high-speed, energy-efficient information processing, with diffractive optical networks emerging as a flexible platform for implementing task-specific ...
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