dc.contributor.author | Lin, SW | |
dc.contributor.author | André, E | |
dc.contributor.author | Dong, JS | |
dc.contributor.author | Sun, J | |
dc.contributor.author | Liu, Y | |
dc.date.accessioned | 2017-10-24T02:45:25Z | |
dc.date.available | 2017-10-24T02:45:25Z | |
dc.date.issued | 2011 | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.doi | 10.1007/978-3-642-24372-1_35 | |
dc.identifier.uri | http://hdl.handle.net/10072/172921 | |
dc.description.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. | |
dc.description.peerreviewed | Yes | |
dc.language | English | |
dc.language.iso | eng | |
dc.publisher | Springer | |
dc.relation.ispartofpagefrom | 463 | |
dc.relation.ispartofpageto | 472 | |
dc.relation.ispartofjournal | Lecture Notes in Computer Science | |
dc.relation.ispartofvolume | 6996 LNCS | |
dc.subject.fieldofresearch | Software engineering not elsewhere classified | |
dc.subject.fieldofresearchcode | 461299 | |
dc.title | An efficient algorithm for learning event-recording automata | |
dc.type | Journal article | |
dc.type.description | C1 - Articles | |
dc.type.code | C - Journal Articles | |
gro.hasfulltext | No Full Text | |
gro.griffith.author | Dong, Jin-Song | |