Machine learning device, robot controller, robot system, and machine learning method for learning action pattern of human

A machine learning method, comprising:

• obtaining a state variable representing a state of a robot when a human and the robot work cooperatively;
• obtaining determination data for a level of burden on the human, wherein the level of burden varies based on an action of the robot;
• setting a reward based on the determination data;
• and
• updating a neural network representing a function for setting the action of the robot, based on the state variable and the reward,
• wherein the reward becomes greater for a smaller value of the level of burden, and the neural network is updated to set the action of the robot that leads to a smaller level of burden on the human.

A robot, comprising:

• at least one memory;
• and
• at least one processor configured to:
• obtain a state variable representing a state of the robot when a human and the robot work cooperatively,
• obtain an output from a neural network having the state variable as input information, and
• control, based on the output from the neural network, an action of the robot when the human and the robot work cooperatively,
• wherein the neural network has been updated, based on a reward for burden on another human, to set the action of the robot that leads to a smaller burden on the human.