Electronic Arts Inc.

Electronics Arts, Inc.

Kazi Atif-Uz Zaman

Navid Aghdaie

John Kolen

Mohsen Sardari

Kenneth Alan Moss

Harold Henry Chaput

Mohamed Marwan Mattar

Su Xue

Meng Wu

Sundeep Narravula

Igor Borovikov

Han Liu

Reza Pourabolghasem

Jesse Hans Stokes Harder

Nitish Victor

Daniel Lee Kading

John Christopher Epler

Thomas Murray Perlinski

Graham Francis Scott

Zhengxing Chen

Yiwei Zhao

Caedmon Somers

Fernando De Mesentier Silva

Jason Rupert

Tushar Agarwal

Yunqi Zhao

Preethi Ganeshan

Yu Jin

Ahmad Beirami

Wei Wang

Wolfram Sebastian Starke

Zebin Chen

Dhaval Shah

Meredith Trotter

Jervis Pinto

Qilian Yu

Polina Igorevna Gouskova

Farah Mariam Ali

Mohamed Marwan Abdel Magid Mattar

Bhargav Rajendra

Chinmay Mukund Sumant

Cong Feng

Drew John Zagieboylo

Chetan Nagaraja Rao

Mathieu Guindon

Embodiments of the systems and methods described herein provide a terrain generation and population system that can determine terrain population rules for terrain population objects and features when placing objects and features in a three dimensional virtual space. As such, the terrain generation and population system can generate realistic terrain for use in game. The terrain generation and population system can receive an image, such as a satellite image, and utilize artificial intelligence to perform image segmentation at the pixel level to segment features and/or objects in the image. The game terrain system can automatically detect and apply feature and object masks based on the identified features and/or objects from the image segmentation. The game terrain system can place the features and/or objects in corresponding masks in the three dimensional space according to the application of terrain population rules.

Terrain generation and population system

A video game includes a single player mode where completion of storyline objectives advances the single player storyline. The video game also includes a multiplayer mode where a plurality of players can play on an instance of a multiplayer map. Storyline objectives from the single player mode are selected and made available for completion to players in the multiplayer mode, and the single player storylines can be advanced by players completing respective storyline objectives while playing in the multiplayer mode. Combinations of storyline objectives are selected from pending storyline objectives for players connecting to a multiplayer game for compatibility with multiplayer maps. Constraints can be used to determine compatibility.

Dynamic modifications of single player and multiplayer mode in a video game

A system and method for providing live gameplay updates receives a modification for a videogame, the modification affecting a gameplay aspect of the videogame during execution of the videogame. The system and method determine a target group for deploying the modification. The target group includes first one or more live instances of the videogame. The system and method deploy the modification to the target group and receive gameplay data associated with the gameplay aspect from the target group. The system and method deploy the modification to second one or more live instances of the videogame based at least in part on an analysis of the received gameplay data.

Live gameplay updates

Systems and methods are provided for enhanced animation generation based on generative control models. An example method includes accessing an autoencoder trained based on character control information generated using motion capture data, the character control information indicating, at least, trajectory information associated with the motion capture data, and the autoencoder being trained to reconstruct, via a latent feature space, the character control information. First character control information associated with a trajectory of an in-game character of an electronic game is obtained. A latent feature representation is generated and the latent feature representation is modified. A control signal is output to a motion prediction network for use in updating a character pose of the in-game character.

Enhanced animation generation based on generative control

A persona system determines a player persona for a player of a gaming system based on gameplay information for the user and, for example, performs dynamic content generation or additional product recommendations based on the player persona. The persona system may receive a request for content based on a persona of a player and receive gameplay data associated with gameplay of the player in a plurality of games. The persona system may then generate a player persona of the player based on the gameplay data associated with the gameplay of the player in the plurality of games, determine persona based content based at least in part on a portion of the player persona, and output the persona based content in response to the request.

Persona driven dynamic content framework

Some embodiments herein disclose intelligent priority evaluators configured to perform a method that prioritizes tasks submitted by various users, even if the tasks are similarly classified. The scheduling system can collect, calculate, and use various criteria to determine a reward score in order to prioritize one task over another, such as for dynamic scheduling purposes. This can be performed in addition to or as a replacement for receiving user designations of priority.

Intelligent system for automated allocation of computing resources

Embodiments of an automated fraud detection system are disclosed that can detect user accounts that are engaging in unauthorized activities within a game application. The fraud detection system can provide an automated system that identifies parasitic accounts. The fraud detection system may identify patterns using machine learning based on characteristics, such as gameplay and transaction characteristics, associated with the parasitic user accounts. The fraud detection system may generate a model that can be applied to existing accounts within the game in order to automatically identify users that are engaging in unauthorized activities. The fraud detection system may automatically identify these parasitic accounts and implement appropriate actions to prevent the accounts from impacting legitimate users within the game application.

Fraud detection system

Embodiments of the systems and methods described herein provide a three dimensional reconstruction system that can receive an image from a camera, and then utilize machine learning algorithms to identify objects in the image. The three dimensional reconstruction system can identify a geolocation of a user, identify features of the surrounding area, such as structures or geographic features, and reconstruct the scene including the identified features. The three dimensional reconstruction system can generate three dimensional object data for the features and/or objects, modify the three dimensional objects, arrange the objects in a scene, and render a two dimensional view of the scene.

Three dimensional reconstruction of objects based on geolocation and image data

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.

User-controllable model-driven matchmaking

Systems described herein may automatically and dynamically adjust the amount and type of computing resources usable to execute, process, or perform various tasks associated with a video game. Using one or more machine learning algorithms, a prediction model can be generated that uses the historical and/or current user interaction data obtained by monitoring the users playing the video game. Based on the historical and/or current user interaction data, future user interactions likely to be performed in the future can be predicted. Using the predictions of the users' future interactions, the amount and type of computing resources maintained in the systems can be adjusted such that a proper balance between reducing the consumption of computing resources and reducing the latency experienced by the users of the video game is achieved and maintained.

Predictive execution of distributed game engines

Various aspects of the subject technology relate to systems, methods, and machine-readable media for granting access to a game. The method includes receiving a request to access the game. The method also includes causing to display a set of challenge options representing challenges of varying difficulty levels for a user to select. The method also includes receiving a selection of a challenge option from a user device. The method also includes causing to present a challenge to the user. The method also includes receiving challenge data from the user including interactions with and results of the challenge. The method also includes determining whether the user passed the challenge based on the challenge data. The method also includes executing or enabling execution of the game upon determining that the user passed the challenge. The method also includes providing the user rewards associated with the game for passing the challenge.

Progressive human user detection challenges with rewards

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.

Systems and methods for automatically measuring a video game difficulty

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Foster City, CA, United States of America

Kazi Atif-Uz Zaman