Abstract
Recently, a new academic field, "service engineering" has been very actively investigated. However, there are few effective software tools to simulate and evaluate services designed based on the concept of service engineering. In the past, the authors proposed a service flow simulation method using scene transition nets(STN) which is a graphic modeling and simulation method for discrete-continuous hybrid system. However, this method cannot simulate complex service flows including customers' decision-making. Nowadays, it turned out that mechanism of reinforcement learning concerns behavioral selections of customers. In this paper, the authors propose to develop decision-making processes models of customers and to simulate customers' behaviors and service flows by using reinforcement learning models and STN.
