Learning Mealy Machines with One Timer

F.W. Vaandrager, M. Ebrahimi and R. Bloem. Learning Mealy Machines with One Timer. In Alberto Leporati, Carlos Martin-Vide, Dana Shapira, Claudio Zandron, editors. Language and Automata Theory and Applications - 15th International Conference, LATA 2021, Milan, Italy, March 1-5, 2021, Proceedings. Lecture Notes in Computer Science 12638, pages 157-170, Springer 2021.

Abstract

We present Mealy machines with a single timer (MM1Ts), a class of models that is both sufficiently expressive to describe the real-time behavior of many realistic applications, and can be learned efficiently. We show how learning algorithms for MM1Ts can be obtained via a reduction to the problem of learning Mealy machines. We describe an implementation of an MM1T learner on top of LearnLib, and compare its performance with recent algorithms proposed by Aichernig et al. and An et al. on several realistic benchmarks.

Local copy (pdf)
Version on website publisher