Invention Grant
- Patent Title: Reinforcement learning method in which discount factor is automatically adjusted
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Application No.: US16517488Application Date: 2019-07-19
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Publication No.: US10581885B1Publication Date: 2020-03-03
- Inventor: Sung Taek Oh , Woong Go , Mi Joo Kim , Jae Hyuk Lee , Jun Hyung Park
- Applicant: KOREA INTERNET & SECURITY AGENCY
- Applicant Address: KR Jeollanam-do
- Assignee: KOREA INTERNET & SECURITY AGENCY
- Current Assignee: KOREA INTERNET & SECURITY AGENCY
- Current Assignee Address: KR Jeollanam-do
- Agency: Sheppard Mullin Richter & Hampton LLP
- Priority: KR10-2018-0149567 20181128
- Main IPC: H04L29/06
- IPC: H04L29/06 ; G06N20/00 ; G06N3/04

Abstract:
There is provided a reinforcement learning method in which a discount factor is automatically adjusted, the method being executed by a computing device and comprising repeatedly training a reinforcement learning model, which determines an evaluation result of input data, using the input data, wherein the repeatedly training of the reinforcement learning model comprises obtaining first result data which is output as a result of inputting the input data to the reinforcement learning model. obtaining second result data which is the result of evaluating the input data using a first evaluation model. obtaining a first return which is the result of adding a discount factor to a first reward given in consideration of whether the first result data and the second result data match. training the reinforcement learning model using the first return and automatically adjusting the discount factor by considering the second result data.
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