There is a strong correlation between the number of appropriate behaviors an interactive robot can produce and its perceived intelligence. We propose a robot architecture for implementing a large number of behaviors and a visualizing tool for understanding the developed complex system. Behaviors are designed by using knowledge obtained through cognitive experiments and implemented by using situated recognition. By representing relationships between behaviors, episode rules help to guide the robot in communicating with people in a consistent manner. We have implemented over 100 behaviors and 800 episode rules in a humanoid robot. As a result, the robot could entice people to relate to it interpersonally. An Episode Editor is a tool to support the development of episode rules and to visualize the complex relationships among the behaviors. We consider the visualization is to be necessary for the constructive approach.