Patents by Inventor Jonathan Albert Rein

Jonathan Albert Rein has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 12076638
    Abstract: An imitation learning system may learn how to play a video game based on user interactions by a tester or other user of the video game. The imitation learning system may develop an imitation learning model based, at least in part, on the tester's interaction with the video game and the corresponding state of the video game to determine or predict actions that may be performed when interacting with the video game. The imitation learning system may use the imitation learning model to control automated agents that can play additional instances of the video game. Further, as the user continues to interact with the video game during testing, the imitation learning model may continue to be updated. Thus, the interactions by the automated agents with the video game may, over time, almost mimic the interaction by the user enabling multiple tests of the video game to be performed simultaneously.
    Type: Grant
    Filed: August 12, 2022
    Date of Patent: September 3, 2024
    Assignee: Electronic Arts Inc.
    Inventors: Igor Borovikov, Jesse Hans Stokes Harder, Thomas Patrick O'Neill, Jonathan Albert Rein, Avery H. Lee, Pawel Piotr Wrotek, Graham Michael Parker, David Vincent
  • Publication number: 20230009378
    Abstract: An imitation learning system may learn how to play a video game based on user interactions by a tester or other user of the video game. The imitation learning system may develop an imitation learning model based, at least in part, on the tester's interaction with the video game and the corresponding state of the video game to determine or predict actions that may be performed when interacting with the video game. The imitation learning system may use the imitation learning model to control automated agents that can play additional instances of the video game. Further, as the user continues to interact with the video game during testing, the imitation learning model may continue to be updated. Thus, the interactions by the automated agents with the video game may, over time, almost mimic the interaction by the user enabling multiple tests of the video game to be performed simultaneously.
    Type: Application
    Filed: August 12, 2022
    Publication date: January 12, 2023
    Inventors: Igor Borovikov, Jesse Hans Stokes Harder, Thomas Patrick O'Neill, Jonathan Albert Rein, Avery H. Lee, Pawel Piotr Wrotek, Graham Michael Parker, David Vincent
  • Patent number: 11446570
    Abstract: An imitation learning system may learn how to play a video game based on user interactions by a tester or other user of the video game. The imitation learning system may develop an imitation learning model based, at least in part, on the tester's interaction with the video game and the corresponding state of the video game to determine or predict actions that may be performed when interacting with the video game. The imitation learning system may use the imitation learning model to control automated agents that can play additional instances of the video game. Further, as the user continues to interact with the video game during testing, the imitation learning model may continue to be updated. Thus, the interactions by the automated agents with the video game may, over time, almost mimic the interaction by the user enabling multiple tests of the video game to be performed simultaneously.
    Type: Grant
    Filed: May 8, 2020
    Date of Patent: September 20, 2022
    Assignee: Electronic Arts Inc.
    Inventors: Igor Borovikov, Jesse Hans Stokes Harder, Thomas Patrick O'Neill, Jonathan Albert Rein, Avery H. Lee, Pawel Piotr Wrotek, Graham Michael Parker, David Vincent
  • Publication number: 20210346798
    Abstract: An imitation learning system may learn how to play a video game based on user interactions by a tester or other user of the video game. The imitation learning system may develop an imitation learning model based, at least in part, on the tester's interaction with the video game and the corresponding state of the video game to determine or predict actions that may be performed when interacting with the video game. The imitation learning system may use the imitation learning model to control automated agents that can play additional instances of the video game. Further, as the user continues to interact with the video game during testing, the imitation learning model may continue to be updated. Thus, the interactions by the automated agents with the video game may, over time, almost mimic the interaction by the user enabling multiple tests of the video game to be performed simultaneously.
    Type: Application
    Filed: May 8, 2020
    Publication date: November 11, 2021
    Inventors: Igor Borovikov, Jesse Hans Stokes Harder, Thomas Patrick O'Neill, Jonathan Albert Rein, Avery H. Lee, Pawel Piotr Wrotek, Graham Michael Parker, David Vincent