Invention Grant
- Patent Title: Meta-reinforcement learning gradient estimation with variance reduction
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Application No.: US16395083Application Date: 2019-04-25
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Publication No.: US11922323B2Publication Date: 2024-03-05
- Inventor: Hao Liu
- Applicant: Salesforce, Inc.
- Applicant Address: US CA San Francisco
- Assignee: Salesforce, Inc.
- Current Assignee: Salesforce, Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Haynes and Boone LLP
- Main IPC: G06N3/088
- IPC: G06N3/088 ; G06N3/08

Abstract:
A method for deep reinforcement learning using a neural network model includes receiving a distribution including a plurality of related tasks. Parameters for the reinforcement learning neural network model is trained based on gradient estimation associated with the parameters using samples associated with the plurality of related tasks. Control variates are incorporated into the gradient estimation by automatic differentiation.
Public/Granted literature
- US20200234113A1 Meta-Reinforcement Learning Gradient Estimation with Variance Reduction Public/Granted day:2020-07-23
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