CPC A63F 13/60 (2014.09) [A63F 13/56 (2014.09); A63F 13/67 (2014.09); A63F 13/69 (2014.09)] | 20 Claims |
1. A method comprises:
generating, via a system including a processor, behavioral experience analysis (BEA) tools based on a preference learning model that includes an artificial intelligence (AI) model trained to infer a preference relation between variables of the AI model;
receiving, via the system, game telemetry data from a gaming application associated with game play of a player, wherein the game telemetry data includes pixel data from the gaming application;
generating, via the system, a predicted user motivation by applying the BEA tools to the game telemetry data, wherein the predicted user motivation includes motivation data that indicates motivation scores for the player for each of a plurality of motivation factors associated with a corresponding one of a plurality of different motivations, and wherein each of the motivation scores for the player predicts an amount that the player's behavior while playing the gaming application is motivated by one of the plurality of different motivations; and
facilitating adaptation of the gaming application based on the predicted user motivation.
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