Inferring device, training device, inferring method, and training method

An inferring method comprising:

• inputting at least data about a state of a controlled object and time-series control information for controlling the controlled object, into a trained network that has been trained by machine learning;
• acquiring predicted data about a future state of the controlled object controlled based on the time-series control information, via the trained network;
• and
• outputting, through a backpropagation on at least a part of the trained network based on at least the predicted data about the future state of the controlled object acquired from the trained network, new time-series control information for controlling the controlled object to bring the future state of the controlled object into a target state,
• wherein the trained network comprises
• a second trained network configured to output data based on at least the data about the future state of the controlled object and the time-series control information, and
• a third trained network configured to output the predicted data based on the data output from the second trained network;
• and
• the one or more processors are configured to
• output, via the second trained network, the data based on at least the data about the future state of the controlled object and the time-series control information, and
• output, via the third trained network, the predicted data from the data based on the data output via the second trained network.

An inferring system comprising:

• one or more memories storing a trained network for outputting, based on inputting at least a current state of a controlled object and control information for controlling the controlled object into the trained network, data indicating a predicted future state of the controlled object;
• and
• one or more processors configured to perform a backpropagation of at least a part of the trained network based on the output data output from the trained network, and output a new control information for the controlled object based on the control information inputted into the trained network and data acquired by the backpropagation,
• wherein the trained network comprises
• a second trained network configured to output data based on at least the data about the state of the controlled object and the control information for controlling the controlled object, and
• a third trained network configured to output the data indicating the predicted future state of the controlled object based on the output from the second trained network;
• and
• the one or more processors are configured to
• output, via the second trained network, the data, and
• output, via the third trained network, the data indicating the predicted future state of the controlled object.