Realtime dynamic modification and optimization of gameplay parameters within a video game application

US11413539B2 · kind B2 · utility

Assignee

• Electronic Arts Inc. · US

Inventors

• Navid Aghdaie · San Jose, US
• John Kolen · Rue de l'Église, US
• Mohamed Marwan Mattar · San Francisco, US
• Mohsen Sardari · Redwood City, US
• Su Xue · Fremont, US
• Kazi Atif-Uz Zaman · Foster City, US
• Meng Wu · Sunnyvale, US

Key dates

• Filing date: Jul 22, 2019
• Grant date: Aug 16, 2022
• Expiry date: Jul 22, 2039

Classification

• Technology area (CPC A): Human Necessities
• CPC primary: A63F13/352
• WIPO field: Furniture, games
• WIPO sector: Other fields

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.