| CPC A63F 13/355 (2014.09) [A63F 13/335 (2014.09); A63F 2300/407 (2013.01); A63F 2300/531 (2013.01); A63F 2300/538 (2013.01)] | 9 Claims |
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1. A computing system having a memory to store a distributed game engine and a processor to execute the distributed game engine, the distributed game engine, when executed by the processor, is configured to provision resources for an online game, the distributed game engine comprising:
a resource allocation model constructed using machine learning algorithm with game play training data collected from prior game play session of the online game, the game play training data includes inputs received from users during the prior game play session of the online game, game states of the online game, and success criteria, outputs of the resource allocation model used to identify types of resources and an amount of each type of resource that were required to satisfy different success criteria for the online game;
a resource allocation agent for analyzing the outputs of the resource allocation model to identify an output defining configuration of types of resources and an amount of each type of resource that were assigned to satisfy the success criteria defined for the online game during prior game play sessions, wherein each type of resource identified is configured to process a specific feature of the game play training data of the online game, the specific feature corresponding with a particular functional portion of the distributed game engine; and
a configuration agent to receive update to the configuration of the resources to meet predicted demand for different types of resources in order to satisfy the success criteria defined for the online game during a subsequent game play session,
wherein the distributed game engine is configured to provision the different types and the amount of each of the different types of resources based on the update to the configuration prior to receiving game play requests from users of the online game for the subsequent game play session.
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