公开(公告)号：US20230229929A1

公开(公告)日：2023-07-20

申请号：US18011630

申请日：2021-01-28

Applicant: Google LLC

Inventor： Amir Yazdanbakhsh ,  Yu Zheng ,  Junchao Chen

IPC: G06N3/092 ,  G06N3/098

CPC classification number: G06N3/092 ,  G06N3/098

Abstract: A computing system for performing distributed large scale reinforcement learning with improved efficiency can include a plurality of actor devices, wherein each actor device locally stores a local version of a machine-learned model, wherein each actor device is configured to implement the local version of the machine-learned model at the actor device to determine an action to take in an environment to generate an experience, a server computing system configured to perform one or more learning algorithms to learn an updated version of the machine-learned model based on the experiences generated by the plurality of actor devices, and a hierarchical and distributed data caching system including a plurality of layers of data caches that propagate data descriptive of the updated version of the machine-learned model from the server computing system to the plurality of actor devices to enable each actor device to update its respective local version of the model.