Inductive inference of regular languages based on model inference

Abstract

This paper is concerned with an algorithm for identifying an unknown regular language from examples of its members and non-members. The algorithm is based on the model inference algorithm given by Shapiro. In our setting, however, a given first order language for describing a target logic program has countably many unary predicate symbols: q0, q1, q2, ....On the other hand, the oracle which gives information about the unknown regular language to the inference algorithm has no interpretation for predicates other than the predicate q0. In such a setting, we cannot directly take advantage of the contradiction backtracing algorithm which is one of the most important part for the efficiency of the model inference algorithm. In order to overcome this disadvantage, we develop a method for giving an interpretation for predicates other than the predicate q0 indirectly, which is based on the idea of using the oracle and a one to one mapping from a set of predicates to a set of strings. Furthermore, we propose a model inference algorithm for regular languages using the method, then argue the correctness and the time complexity of the algorithm.