Method, etc. for generating trained model for predicting action to be selected by user

Abstract

One or more embodiments of the invention is a method for generating a trained model for predicting an action to be selected by a user in a game that proceeds in accordance with actions selected by the user, while updating game states, the method including: determining weights for individual history-data element groups; generating training data from data of game states and actions included in the history-data element groups; and generating a trained model on the basis of the generated training data, wherein the generation of training data includes generating a number of items of game state text as game state text corresponding to one game state, having different orders of a plurality of text elements, the number being based on the determined weight, and generating training data including pairs of the individual generated items of game state text and corresponding action text.