A system and method for media-object binding and predicting performance in a media is provided. One or more sets of object data may be associated with the media. One or more media-object bindings between the one or more sets of object data and the media may be formed and stored in one or more databases. The one or more sets of object data may include data about an object displayed during at least the portion of the media. One or more object-object associations between the one or more sets of object data and other stored object data may be formed and stored the one or more databases. The one or more object-object associations may form one or more object aggregations. A determination may for made regarding if any of the one or more object aggregations meet or pass a threshold.

A plan processing program for planning a task executed by a character based on a hierarchical task network causes a server to implement a plan generation function of generating a plan configured with a plurality of tasks from a domain based on goal information, in which in the plan generation function, a function of generating the plan in which a subsequent task to be employed is configured to change in accordance with a state or a condition is implemented.

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.

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.

Data characterizing historical skills-based gaming metrics for a first user and historical skills-based gaming metrics for at least one second user is accessed. Using the accessed data and a set of rules, a targeted advertisement to present to the first user is determined. The targeted advertisement specifies at least one skills-based game and a characterization of the at least one second user's historical skills-based gaming metrics. The targeted advertisement is generated. Data characterizing the targeted advertisement is provided. Related apparatus, systems, techniques, and articles are also described.

In a gaming environment including an aggregation platform, remote game servers (RGS) and Gaming Platform as a Service (GPAS), a method for operating an aggregation platform in a gaming environment. The method including associating a player with tokens and features, where the tokens are usable to acquire the features, monitoring operation of the player with the tokens in the games, and determining operation of Features in the games, based upon the operation of the player with the tokens.

Systems, storage media and apparatus for voice separated server architecture for privacy of a plurality of users of a massively multiplayer online game (MMOG) enabling a gaming computing environment that is separate from a voice channel for the plurality of users of the massively multiplayer online game (MMOG) are disclosed. Some embodiments may include: communicating with a gaming server for a Massively Multiplayer Online Game, the gaming server enabling a Massively Multiplayer Online Game environment, communicating with a voice server for the Massively Multiplayer Online Game, the voice server for the Massively Multiplayer Online Game being completely separate from the gaming server enabling privacy for the plurality of users of the massively multiplayer online game, and providing a MMOG primary voice channel, integrating the MMOG primary voice channel and the Massively Multiplayer Online Game environment, enabling a subsection of the plurality of users to verbally communicate.

A data processing device according to an aspect of the present invention includes a reception unit, a generation unit, and a transmission unit. The reception unit receives operation requests with respect to an application from an arbitrary number of application execution devices executing the application. The generation unit generates application operation data that includes operation input data for the application and time data indicating the time when the relevant operation input data is applied to the application. The transmission unit transmits the application operation data to the arbitrary number of application execution devices. When an operation request is received from one or more of the arbitrary number of application execution devices, the generation unit generates operation input data on the basis of the relevant operation request.

A data processing device according to an aspect of the present invention includes a reception unit, a generation unit, and a transmission unit. The reception unit receives operation requests with respect to an application from an arbitrary number of application execution devices executing the application. The generation unit generates application operation data that includes operation input data for the application and time data indicating the time when the relevant operation input data is applied to the application. The transmission unit transmits the application operation data to the arbitrary number of application execution devices. When an operation request is received from one or more of the arbitrary number of application execution devices, the generation unit generates operation input data on the basis of the relevant operation request.

Systems and methods for reducing latency through motion estimation and compensation techniques are disclosed. The systems and methods include a client device that uses transmitted lookup tables from a remote server to match user input to motion vectors, and tag and sum those motion vectors. When a remote server transmits encoded video frames to the client, the client decodes those video frames and applies the summed motion vectors to the decoded frames to estimate motion in those frames. In certain embodiments, the systems and methods generate motion vectors at a server based on predetermined criteria and transmit the generated motion vectors and one or more invalidators to a client, which caches those motion vectors and invalidators. The server instructs the client to receive input from a user, and use that input to match to cached motion vectors or invalidators. Based on that comparison, the client then applies the matched motion vectors or invalidators to effect motion compensation in a graphic interface. In other embodiments, the systems and methods cache repetitive motion vectors at a server, which transmits a previously generated motion vector library to a client. The client stores the motion vector library, and monitors for user input data. The server instructs the client to calculate a motion estimate from the input data and instructs the client to update the stored motion vector library based on the input data, so that the client applies the stored motion vector library to initiate motion in a graphic interface prior to receiving actual motion vector data from the server. In this manner, latency in video data streams is reduced.