Mutual learning of multi-consciousness agents,including an ego for an autonomous vehicle

In this paper, we propose a multi-agent learning system for the control of an intelligent robot, based on a model of the human consciousnesses, including the ego. We pay attention to the intelligent learning processes of human beings. We try to give a robot a high learning ability by modeling the roles of the human consciousnesses, including the ego. In most ordinary methods, the instructions for learning are given from outside the system only. In the proposed method, the instructions are given not only from outside, but also from inside (from other agents in the system). Therefore, the robot can learn efficiently because it has more instructions than usual. The learning is also more flexible, since an agent learns by instructions from other agents while the learning agent and one of the instructing agents exchange roles according to changes in the environment. We experimentally verified that the proposed method is efficient by using an actual robot.