Reinforcement learning in robotic process automation

Reinforcement learning may be used to train machine learning (ML) models for robotic process automation (RPA) that are implemented by robots. A policy network may be employed, which learns to achieve a definite output by providing a particular input. In other words, the policy network informs the sy...

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Bibliographic Details
Main Authors Singh, Prabhdeep, Hidalgo, Marco Alban
Format Patent
LanguageEnglish
Published 03.10.2023
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:Reinforcement learning may be used to train machine learning (ML) models for robotic process automation (RPA) that are implemented by robots. A policy network may be employed, which learns to achieve a definite output by providing a particular input. In other words, the policy network informs the system whether it is getting closer to the winning state. The policy network may be refined by the robots automatically or with the periodic assistance of a human in order to reach the winning state, or to achieve a more optimal winning state. Robots may also create other robots that utilize reinforcement learning.
Bibliography:Application Number: US201916707858