Intrinsically motivated extreme learning machine autonomous development system and operating method thereof

The invention belongs to the technical field of intelligent robots, and concretely relates to an intrinsically motivated extreme learning machine autonomous development system and an operating method thereof. The autonomous development system comprises an inner state set, a motion set, a state transition function, an intrinsic motivation orientation function, a reward signal, a reinforced learning update iteration formula, an evaluation function and a motion selection probability. According to the invention, an intrinsic motivation signal is utilized to simulate an orientation cognitive mechanism of the interest of people in things so that a robot can finish relevant tasks voluntarily, thereby solving a problem that the robot is poor in self-learning. Furthermore, an extreme learning machine network is utilized to practice learning and store knowledge and experience so that the robot, if an experience fails, can use the stored knowledge and experience to keep exploring instead of learning from the beginning.