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|Title:||An efficient algorithm for learning event-recording automata|
|Authors:||Lin, S.-W. |
|Source:||Lin, S.-W.,André, É.,Dong, J.S.,Sun, J.,Liu, Y. (2011). An efficient algorithm for learning event-recording automata. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6996 LNCS : 463-472. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-24372-1_35|
|Abstract:||In inference of untimed regular languages, given an unknown language to be inferred, an automaton is constructed to accept the unknown language from answers to a set of membership queries each of which asks whether a string is contained in the unknown language. One of the most well-known regular inference algorithms is the L* algorithm, proposed by Angluin in 1987, which can learn a minimal deterministic finite automaton (DFA) to accept the unknown language. In this work, we propose an efficient polynomial time learning algorithm, TL*, for timed regular language accepted by event-recording automata. Given an unknown timed regular language, TL* first learns a DFA accepting the untimed version of the timed language, and then passively refines the DFA by adding time constraints. We prove the correctness, termination, and minimality of the proposed TL* algorithm. © 2011 Springer-Verlag.|
|Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Appears in Collections:||Staff Publications|
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