Machine learning models for implementing animation actions

An animation development method, comprising:

• identifying, by one or more processors and based at least in part on analyzing movement of an object in an animation in a video game, an event that transpires in the animation;
• determining, by the one or more processors, a parameter value associated with the event;
• identifying, by the one or more processors, an outcome associated with the event;
• generating, by the one or more processors, training data associated with the video game and based at least in part on the parameter value and the outcome;
• generating, by the one or more processors, a predictive model based at least in part on the training data;
• and
• deploying the predictive model in the video game to predict one or more second outcomes corresponding to one or more second events that transpire during video game play of the video game.

A system, comprising:

• one or more processors;
• and
• one or more computer-readable media storing computer-executable instructions that, when executed by the one or more processors, cause the one or more processors to:
• receive a first input during a video game play of a video game, the first input corresponding to a first object rendered in the video game;
• receive a second input during the video game play of the video game, the second input corresponding to a second object rendered in the video game;
• determine an occurrence of an event in the video game based at least in part on the first input and the second input;
• identify a predictive model associated with the event, the predictive model comprising a machine learning model trained on previous video game play training data associated with the video game;
• determine, based at least in part on the predictive model, an outcome in the video game associated with the event;
• and
• render, based at least in part on the outcome, an animation action on at least one of the first object or the second object.