An algorithm for learning real-time automata

An algorithm for learning real-time automata

Verwer, S.E.
De Weerdt, M.M.
Witteveen, C.

Electrical Engineering, Mathematics and Computer Science

Software Computer Technology

2007-05-14

We describe an algorithm for learning simple timed automata, known as real-time automata. The transitions of real-time automata can have a temporal constraint on the time of occurrence of the current symbol relative to the previous symbol. The learning algorithm is similar to the redblue fringe state-merging algorithm for the problem of learning deterministic finite automata. In addition to state merges, our algorithm can perform state splits by making use of the time values in the input data. We tested our learning algorithm on randomly generated problems. The results are promising and show that learning a real-time automaton directly from timed data outperforms a method that uses sampling in order to deal with the timed data.

http://resolver.tudelft.nl/uuid:a202b4cf-5153-4ad5-b41d-5d0332bf04f2

Benelearn 2007: Proceedings of the Annual Machine Learning Conference of Belgium and the Netherlands, Amsterdam, The Netherlands, 14-15 May 2007

Institutional Repository

conference paper

(c) 2007 The Author(s)