公开(公告)号：US20230259765A1

公开(公告)日：2023-08-17

申请号：US18056331

申请日：2022-11-17

Applicant: Intel Corporation

Inventor： Nicolas Sawaya ,  Subrata Goswami ,  Christopher Hughes

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: An agent trained using reinforcement learning (RL) can be used to determine a structure for a complex tensor network. The agent makes incremental changes to a tensor network according to a policy model, where parameters of the policy model were trained using RL. The agent may use a cost function to assess the changes, e.g., to determine whether or not to keep a particular modification. In some cases, tensor networks determined using the RL agent can be used to train a model that can more efficiently select a structure for a complex tensor network.