We show how an autonomous mobile robot can acquire the optimal action through the interaction with the real world. We propose a new architecture using the hierarchical fuzzy rules, fuzzy evaluation system and learning automaton. By using our proposed method, the robot acquires how to approach the goal avoiding a moving obstacle, using the steering and velocity control inputs, simultaneously. We also show the experimental results to confirm the feasibility of our method.