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US Patent 10235192 Self-learning robotic process automation

Patent 10235192 was granted and assigned to Accenture on March, 2019 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
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Patent attributes

Patent Applicant
Accenture
Accenture
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Current Assignee
Accenture
Accenture
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
102351920
Patent Inventor Names
Vitalie Schiopu0
Adrien Jacquot0
Jeroen van den Heuvel0
Simon Hall0
Date of Patent
March 19, 2019
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Patent Application Number
156320990
Date Filed
June 23, 2017
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Patent Citations Received
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US Patent 12118043 Robotic process automation (RPA) comprising automatic document scrolling
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US Patent 11487563 Multi-anchor based extraction, recognition, and machine learning of user interface (UI)
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US Patent 11782759 Prioritized data object processing under processing time constraints
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US Patent 11789853 Test automation for robotic process automation
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US Patent 11803397 Determining sequences of interactions, process extraction, and robot generation using artificial intelligence / machine learning models
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US Patent 11449359 Prioritized data object processing under processing time constraints
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US Patent 11921608 Identifying a process and generating a process diagram
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US Patent 11983379 Multi-anchor based extraction, recognition, and machine learning of user interface (UI)
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...
Patent Primary Examiner
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Gabriel Chu
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Patent abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for a self-learning robotic process automation are disclosed. In one aspect, a method includes receiving an automated script that includes one or more commands and that is configured to interact with graphical elements that appear on a user interface. The method further includes executing a command of the one or more commands of the automated script. The method further includes determining that an error occurred during execution of the command of the one or more commands of the automated script. The method further includes determining a modification for the command by applying a script repair model. The method further includes executing the modified command. The method further includes determining whether the error or another error occurred during execution of the modified command. The method further includes determining whether to update the automated script with the modified command.

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