Predicting the further development of a scenario with aggregation of latent representations

A method for training a context encoder and/or a processing function and/or a context predictor, for predicting a future state and/or behavior of a scenario, comprising the following steps:

• providing measured observations Ot of observable variables at points in time t in a specified measurement time horizon t≤M;
• based on a subset of the measured observations Ot in a specified test time horizon t≤T with T<M, determining a prediction of a future state and/or behavior of a scenario;
• assessing, using a specified cost function, how well the prediction of the future state and/or behavior, and/or at least one subsequent result determined from the prediction of the future state and/or behavior, is consistent with the observations in the time horizon T<t≤M;
• and
• optimizing parameters which characterize a behavior of the context encoder and/or the processing function and/or the context predictor with a goal of improving the assessment by the cost function as predictions of the future state and/or behavior continue to be determined.

A non-transitory machine-readable data carrier on which is stored one or more computer programs for predicting a future state and/or behavior of a scenario whose further development is correlated with one or more observable variables, without directly and unambiguously arising from the observable variables, the one or more computer programs, when executed by one or more computers and/or compute instances, cause the one or more computers and/or compute instances to perform the following steps of:

• processing measured observations of the observable variables at a current points in time t using an encoder to form context representations of the scenario;
• processing the context representations using a specified processing function to form processing products;
• determining predictions for the context representations of the scenario at future points in time t using a context predictor based on at least the processing products as the prediction of the future state and/or behavior;
• wherein the specified processing function is configured to aggregate the context representations from a specified time horizon prior to the point in time t to form the processing product.

One or more computers and/or compute instances configured to predict a future state and/or behavior of a scenario whose further development is correlated with one or more observable variables, without directly and unambiguously arising from the observable variables, the one or more computers and/or compute instances configured to:

• process measured observations of the observable variables at a current points in time t using an encoder to form context representations of the scenario;
• process the context representations using a specified processing function to form processing products;
• determine predictions for the context representations of the scenario at future points in time τ using a context predictor based on at least the processing products as the prediction of the future state and/or behavior;
• wherein the specified processing function is configured to aggregate the context representations from a specified time horizon prior to the point in time t to form the processing product.