Memory Device With Reinforcement Learning With Q-Learning Acceleration

Abstract

The present disclosure generally relates to data storage devices, such as solid state drives. A data storage device includes a controller, one or more volatile memory locations, and one or more non-volatile memory locations. Computations, including reinforcement learning algorithms, may be completed by the controller using the one or more non-volatile memory locations. Data associated with reinforcement learning is stored in a table on one or more planes of the non-volatile memory, where the results from the computations update the table with the relevant values. The data in the table are aligned to one or more wordlines, such that sensing the wordline senses all the data stored in the table.

Dependencies are inferred from the claim text.