Systems and methods for monitoring gameplay for monitoring real-time gameplay object data that is used to extract patterns in gameplay for generating notifications regarding control options based on extracted patterns. The notifications may indicate that selected conditions may be met based on the activity data that may be analyzed based on learning models associated with the selected conditions. The learning models may include models regarding player behavior, such as bullying or harassing language. The extract patterns may include gameplay session length, type of game played, and in-game behavior. Supervising accounts may receive recorded media segments associated with the activity data that met the selected conditions. And the user accounts engaging in such activities may be blocked and/or provided suggestions regarding alternative activities.

Systems and methods for monitoring gameplay for monitoring real-time gameplay object data that is used to extract patterns in gameplay for generating notifications regarding control options based on extracted patterns. The notifications may indicate that selected conditions may be met based on the activity data that may be analyzed based on learning models associated with the selected conditions. The learning models may include models regarding player behavior, such as bullying or harassing language. The extract patterns may include gameplay session length, type of game played, and in-game behavior. Supervising accounts may receive recorded media segments associated with the activity data that met the selected conditions. And the user accounts engaging in such activities may be blocked and/or provided suggestions regarding alternative activities.

Systems and methods are described herein for monitoring a gameplay session for violations of a policy and creating a remediation gameplay session through which remediation can be provided to players or player accounts that violate gameplay policies. The systems and methods can create a remediation gameplay session based in part on the game state data of the gameplay session during which the violation occurs.

Systems and methods are described herein for monitoring a gameplay session for violations of a policy and creating a remediation gameplay session through which remediation can be provided to players or player accounts that violate gameplay policies. The systems and methods can create a remediation gameplay session based in part on the game state data of the gameplay session during which the violation occurs.

A system for customizing an end user gaming experience is disclosed herein. The system includes a processor. The processor is configured to create a campaign by receiving a campaign creation request from an end user device, the campaign creation request comprising one or more parameters of a campaign associated with the campaign request, creating the campaign based on the one or more parameters associated with the campaign request, and personalizing one or more offers for an end user, each of the one or more offers comprising a game having one or more hurdles, wherein completion of each of the one or more hurdles leads to a reward. The processor is further configured to map a subset of the one or more personalized offers to the end user. The processor is further configured to monitor progress of the campaign.

An example device comprises: a head-mounted display; a housing for the head-mounted display, the housing including an external surface; sensors to monitor a wearer of the head-mounted display; a visual indicator at the external surface; and a controller. The controller is generally to: control subsets of the sensors to be on or off based on respective permissions for usage of subsets of the sensors; and control the visual indicator to indicate respective status of the subsets of the sensors.

A computer-implemented method is provided of allowing a user to automatically transform domain knowledge into a machine learning model to be used in real-time operation of video games. The method comprises providing a user interface which allows a user to define domain knowledge relating to a video game by specifying one or more labeling functions; transforming the labeling functions into executable code; labeling raw data relating to the video game using the executable code to obtain labeled data; and applying an automated machine learning module to the labeled data to obtain a machine learning model.

A computer-implemented method is provided of allowing a user to automatically transform domain knowledge into a machine learning model to be used in real-time operation of video games. The method comprises providing a user interface which allows a user to define domain knowledge relating to a video game by specifying one or more labeling functions; transforming the labeling functions into executable code; labeling raw data relating to the video game using the executable code to obtain labeled data; and applying an automated machine learning module to the labeled data to obtain a machine learning model.

Systems and methods are described herein for monitoring a gameplay session for violations of a policy and creating a remediation gameplay session through which remediation can be provided to players or player accounts that violate gameplay policies. The systems and methods can create a remediation gameplay session based in part on the game state data of the gameplay session during which the violation occurs.

Systems and methods are described herein for monitoring a gameplay session for violations of a policy and creating a remediation gameplay session through which remediation can be provided to players or player accounts that violate gameplay policies. The systems and methods can create a remediation gameplay session based in part on the game state data of the gameplay session during which the violation occurs.