The minimum consistent DFA problem cannot be approximated within any polynomial
Journal of the ACM (JACM)
Theoretical Computer Science
Characteristic Sets for Polynomial Grammatical Inference
Machine Learning
Event-clock automata: a determinizable class of timed automata
Theoretical Computer Science
Introduction to the Theory of Computation: Preliminary Edition
Introduction to the Theory of Computation: Preliminary Edition
ICGI '98 Proceedings of the 4th International Colloquium on Grammatical Inference
On the Relationship between Models for Learning in Helpful Environments
ICGI '00 Proceedings of the 5th International Colloquium on Grammatical Inference: Algorithms and Applications
Inference of event-recording automata using timed decision trees
CONCUR'06 Proceedings of the 17th international conference on Concurrency Theory
One-Clock Deterministic Timed Automata Are Efficiently Identifiable in the Limit
LATA '09 Proceedings of the 3rd International Conference on Language and Automata Theory and Applications
Hi-index | 0.00 |
We study the complexity of identifying (learning) timed automata in the limit from data. Timed automata are finite state models that model time explicitly, i.e., using numbers. Because timed automata use numbers to represent time, they can be exponentially more compact than models that model time implicitly, i.e., using states.We show three results that are essential in order to exactly determine when timed automata are efficiently identifiable in the limit. First, we show that polynomial distinguishability is a necessary condition for efficient identifiability in the limit. Second, we prove that deterministic time automata with two or more clocks are not polynomially distinguishable. As a consequence, they are not efficiently identifiable. Last but not least, we prove that deterministic timed automata with one clock are polynomially distinguishable, which makes them very likely to be efficiently identifiable in the limit.