a trained model which is built by being trained on work data when a human operates a robot so that the robot performs a series of operations, the work data including input data and output data, the input data being the state of the robot and its surroundings, the output data being the corresponding human operation or the operation of the robot by the human operation;

a control data acquisition section which acquires control data of the robot to make the robot perform the work, in the case the input data concerning the state of the robot and its surroundings is input to the trained model, by acquiring output data concerning the human operation or the operation of the robot predicted accordingly from the trained model;

base trained models, each of the base trained models being built by being trained on work data when a human operates the robot so that the robot performs an operation decomposed from the series of operations, and being built for each of a plurality of operations decomposed from the series of operations, the work data including input data and output data, the input data being the state of the robot and its surroundings, the output data being the corresponding human operation or the operation of the robot by the human operation;

an operation label storage section which stores operation labels, each of the operation labels including information expressing the operation and being stored in correspondence with the base trained model;

a base trained model combination information acquisition section which acquires combination information when the trained model is represented by a combination of a plurality of the base trained models, by acquiring a similarity between the trained model and the respective base trained models; and

an information output section that outputs the operation label corresponding to each of the plurality of the base trained models which are combined to represent the trained model based on the combination information.