Mental State Transition Network which consists of mental states connected one another is a
basic concept of approximating to human psychological and mental responses. It can represent transi-
tion from an emotional state to other one with stimulus by calculating Emotion Generating Calculations
method. In this paper, we try to investigate the relation between emotion type derived by EGC and the
transition in MSTN through the empirical studies. In this paper, the agent using Mental State Transition
Network can interact with human to realize smooth communication by the reinforcement learning methods.