Synthesis of supervisors using learning algorithm of regular languages

We propose an algorithm for the synthesis of supervisors in discrete event systems. The algorithm is based on a learning algorithm of regular language s proposed by Angluin, and constructs a supervisor realizing an unknown spe cification which is identified through the interaction between the designer and the algorithm. We also consider the synthesis problem for systems cons isting of several processes which behave concurrently. One of serious probl ems in dealing with such a concurrent system is that the number of states r equired for describing the global behavior often grows exponentially in the size of the model. To improve this situation, we introduce the concept of dependency defined on the set of events. It prevents the algorithm from con sidering all interleavings of independent occurrences of events.