Identifying an automaton model for timed data

Identifying an automaton model for timed data

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

Electrical Engineering, Mathematics and Computer Science

Software Computer Technology

2006-05-11

A model for discrete event systems (DES) can be learned from observations. We propose a simple type of timed automaton to model DES where the timing of the events is important. Learning such an automaton is proven to be NP-complete by a reduction from the problem of learning deterministic finite state automata (DFA) without time. Based on this reduction, we show how the currently best learning algorithm for DFAs (state merging) can be adapted to deal with time information.

http://resolver.tudelft.nl/uuid:faab7982-46bf-4d52-8a2a-324a88542584

Benelearn 2006: Proceedings of the 15th Annual Machine Learning Conference of Belgium and the Netherlands, Ghent, Belgium, 11-12 May 2006

Institutional Repository

conference paper

(c) 2006 The Author(s)