公开(公告)号：US11458399B2

公开(公告)日：2022-10-04

申请号：US17068315

申请日：2020-10-12

Applicant: Electronic Arts Inc.

Inventor： Navid Aghdaie ,  John Kolen ,  Mohamed Marwan Mattar ,  Mohsen Sardari ,  Su Xue ,  Kazi Atif-Uz Zaman ,  Meng Wu

IPC: A63F13/67 ,  A63F13/537 ,  A63F13/822

Abstract: Embodiments of the systems and methods described herein can automatically measure the difficulty metrics associated with various aspects of a video game using an artificial intelligence system. The artificial intelligence system may include multiple game agents. Telemetry data associated with the gameplay of each game agent may be recorded while the game application is automatically executed by the game agents. The telemetry data may be communicated to a data analysis system which can calculate game difficulty metrics for various aspects of the game. The data analysis system can determine game difficulty associated with the various aspects based on the game difficulty metrics. The results from the data analysis system may be visualized and communicated to a game developer for updating the operations of the video game.

公开(公告)号：US10384133B1

公开(公告)日：2019-08-20

申请号：US15395949

申请日：2016-12-30

Applicant: Electronic Arts Inc.

Inventor： Navid Aghdaie ,  John Kolen ,  Mohamed Marwan Mattar ,  Mohsen Sardari ,  Su Xue ,  Kazi Atif-Uz Zaman ,  Meng Wu

IPC: A63F13/67 ,  A63F13/822 ,  A63F13/537

Abstract: Embodiments of the systems and methods described herein can automatically measure the difficulty metrics associated with various aspects of a video game using an artificial intelligence system. The artificial intelligence system may include multiple game agents. Telemetry data associated with the gameplay of each game agent may be recorded while the game application is automatically executed by the game agents. The telemetry data may be communicated to a data analysis system which can calculate game difficulty metrics for various aspects of the game. The data analysis system can determine game difficulty associated with the various aspects based on the game difficulty metrics. The results from the data analysis system may be visualized and communicated to a game developer for updating the operations of the video game.

公开(公告)号：US20180243656A1

公开(公告)日：2018-08-30

申请号：US15445784

申请日：2017-02-28

Applicant: Electronic Arts Inc.

Inventor： Navid Aghdaie ,  John Kolen ,  Mohamed Marwan Mattar ,  Mohsen Sardari ,  Su Xue ,  Kazi Atif-Uz Zaman ,  Meng Wu

IPC: A63F13/67 ,  A63F13/79

CPC classification number: A63F13/67 ,  A63F13/79

Abstract: Embodiments presented herein include systems and methods for performing dynamic difficulty adjustment. Further, embodiments disclosed herein perform dynamic difficulty adjustment using processes that may not be detectable or are more difficult to detect by users compared to static and/or existing difficulty adjustment processes. In some embodiments, historical user information utilized by a machine learning system to generate a prediction model that predicts an expected duration of game play, such as for example, an expected churn rate, a retention rate, the length of time a user is expected to play the game, or an indication of the user's expected game play time relative to a historical set of users who have previously played the game. Before or during game play, the prediction model can be applied to information about the user to predict the user's expected duration of game play. Based on the expected duration, in some embodiments, the system may then utilize a mapping data repository to determine how to dynamically adjust the difficulty of the game, such as, for example, changing the values of one or more gameplay parameters to make portions of the game less difficult.

公开(公告)号：US11413539B2

公开(公告)日：2022-08-16

申请号：US16518914

申请日：2019-07-22

Applicant: Electronic Arts Inc.

Inventor： Navid Aghdaie ,  John Kolen ,  Mohamed Marwan Mattar ,  Mohsen Sardari ,  Su Xue ,  Kazi Atif-Uz Zaman ,  Meng Wu

IPC: A63F13/67 ,  A63F13/79 ,  A63F13/31 ,  A63F13/352

Abstract: Embodiments presented herein include systems and methods for performing dynamic difficulty adjustment. Further, embodiments disclosed herein perform dynamic difficulty adjustment using processes that may not be detectable or are more difficult to detect by users compared to static and/or existing difficulty adjustment processes. In some embodiments, historical user information utilized by a machine learning system to generate a prediction model that predicts an expected duration of game play, such as for example, an expected churn rate, a retention rate, the length of time a user is expected to play the game, or an indication of the user's expected game play time relative to a historical set of users who have previously played the game. Before or during game play, the prediction model can be applied to information about the user to predict the user's expected duration of game play. Based on the expected duration, in some embodiments, the system may then utilize a mapping data repository to determine how to dynamically adjust the difficulty of the game, such as, for example, changing the values of one or more gameplay parameters to make portions of the game less difficult.

公开(公告)号：US20220054943A1

公开(公告)日：2022-02-24

申请号：US16999444

申请日：2020-08-21

Applicant: Electronic Arts Inc.

Inventor： Meng Wu ,  Harold Chaput ,  Navid Aghdaie ,  Kazi Zaman ,  Yunqi Zhao ,  Qilian Yu

IPC: A63F13/57 ,  G06N20/00

Abstract: According to a first aspect of this specification, there is disclosed a computer implemented method comprising: training, based on an initial behavior goal and using reinforcement-learning, a reinforcement-learning model for controlling behavior of a non-playable character in a computer game environment; converting the trained reinforcement-learning model into a behavior tree model for controlling behavior of the non-playable character; editing, based on a user input, the behavior tree model to generate an updated behavior tree model for controlling behavior of the non-playable character; and outputting a final model for controlling non-player character behavior for use in the computer game environment, wherein the model for controlling non-player character behavior is based at least in part on the updated behavior tree model.

公开(公告)号：US20200078685A1

公开(公告)日：2020-03-12

申请号：US16518914

申请日：2019-07-22

Applicant: Electronic Arts Inc.

Inventor： Navid Aghdaie ,  John Kolen ,  Mohamed Marwan Mattar ,  Mohsen Sardari ,  Su Xue ,  Kazi Atif-Uz Zaman ,  Meng Wu

IPC: A63F13/67 ,  A63F13/79

Abstract: Embodiments presented herein include systems and methods for performing dynamic difficulty adjustment. Further, embodiments disclosed herein perform dynamic difficulty adjustment using processes that may not be detectable or are more difficult to detect by users compared to static and/or existing difficulty adjustment processes. In some embodiments, historical user information utilized by a machine learning system to generate a prediction model that predicts an expected duration of game play, such as for example, an expected churn rate, a retention rate, the length of time a user is expected to play the game, or an indication of the user's expected game play time relative to a historical set of users who have previously played the game. Before or during game play, the prediction model can be applied to information about the user to predict the user's expected duration of game play. Based on the expected duration, in some embodiments, the system may then utilize a mapping data repository to determine how to dynamically adjust the difficulty of the game, such as, for example, changing the values of one or more gameplay parameters to make portions of the game less difficult.

公开(公告)号：US11204742B1

公开(公告)日：2021-12-21

申请号：US15940814

申请日：2018-03-29

Applicant: Electronic Arts Inc.

Inventor： Meng Wu ,  John Kolen ,  Navid Aghdaie ,  Kazi Atif-Uz Zaman

IPC: G06F8/38 ,  G06Q30/02

Abstract: Methods for providing multi-objective experiments with dynamic group assignment are provided. In one aspect, a method includes receiving, from a configuration component of an experiment management system, a plurality of objectives and at least one constraint for an experiment. The method also includes assigning a test population of the experiment into a plurality of groups. The method also includes determining a progress summary that predicts completion rates for the plurality of objectives according to the at least one constraint. The method also includes modifying a prioritization of the plurality of objectives to optimize the predicted completion rates. The method also includes receiving a request to add additional users into the test population. The method also includes distributing the additional users into the plurality of groups according to the modified prioritization. Systems and machine-readable media are also provided.

公开(公告)号：US11478715B1

公开(公告)日：2022-10-25

申请号：US16908421

申请日：2020-06-22

Applicant: Electronic Arts Inc.

Inventor： Meng Wu ,  Qilian Yu ,  Harold Henry Chaput ,  Navid Aghdaie ,  Kazi Atif-Uz Zaman ,  Kenneth Alan Moss

IPC: A63F13/798 ,  A63F13/795 ,  A63F13/352 ,  A63F13/67 ,  G06N20/20 ,  G06N3/08

Abstract: Various aspects of the subject technology relate to systems, methods, and machine-readable media for user matchmaking. The method includes training a quality model and an embedding model based on historical data and user control options. The method also includes receiving user control options and matchmaking requests from users. The method also includes embedding, through the embedding model, user data regarding the users into an embedded space based on the received user control options and the matchmaking requests. The method also includes determining, based on the embedded user data, that a distance between two users satisfies a distance threshold. The method also includes matching the two users when the determined distance satisfies the distance threshold.

公开(公告)号：US20200030700A1

公开(公告)日：2020-01-30

申请号：US16532301

申请日：2019-08-05

Applicant: Electronic Arts Inc.

Inventor： Mohamed Marwan Mattar ,  Meng Wu ,  John Kolen ,  Navid Aghdaie ,  Kazi Atif-Uz Zaman

IPC: A63F13/5378 ,  A63F13/35 ,  A63F13/79 ,  G06N20/00 ,  G06F16/29 ,  G06F16/955 ,  G06F16/9535

Abstract: The present disclosure provides embodiments of a virtual mapping system for using real world geographical locations to generate virtual environments within game applications. The virtual mapping system allows a game application to identify geographical information associated with real world locations. The geographical information can be used by the game application to recreate the selected geographical location using virtual assets from the game application.

公开(公告)号：US20190381407A1

公开(公告)日：2019-12-19

申请号：US16455448

申请日：2019-06-27

Applicant: Electronic Arts Inc.

Inventor： Navid Aghdaie ,  John Kolen ,  Mohamed Marwan Mattar ,  Mohsen Sardari ,  Su Xue ,  Kazi Atif-Uz Zaman ,  Meng Wu

IPC: A63F13/67 ,  A63F13/537 ,  A63F13/822

Abstract: Embodiments of the systems and methods described herein can automatically measure the difficulty metrics associated with various aspects of a video game using an artificial intelligence system. The artificial intelligence system may include multiple game agents. Telemetry data associated with the gameplay of each game agent may be recorded while the game application is automatically executed by the game agents. The telemetry data may be communicated to a data analysis system which can calculate game difficulty metrics for various aspects of the game. The data analysis system can determine game difficulty associated with the various aspects based on the game difficulty metrics. The results from the data analysis system may be visualized and communicated to a game developer for updating the operations of the video game.