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--- start [2019/01/08 11:07] – [Active Automata Learning Background Knowledge] liyong
+++ start [2020/12/16 14:25] – [Active Automata Learning Background Knowledge] liyong
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 ===== Active Automata Learning Background Knowledge =====
-In the active automata learning setting proposed by Angluin [1], there is a //teacher//, which knows the target language //L//, and a //learner//, whose task is to learn from the teacher the target language, represented by an automaton.
+In the active automata learning setting proposed by Angluin [1], there is a //teacher//, who knows the target language //L//, and a //learner//, whose task is to learn from the teacher the target language, represented by an automaton.
 The learner interacts with the teacher by means of two kinds of queries: //membership queries// and //equivalence queries//.
 A membership query //MQ[w]// asks whether a string //w// belongs to //L// while an equivalence query //EQ[A]// asks whether the hypothesis automaton //A// recognizes //L//.
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 [8] Radu Grosu, Scott A. Smolka. "Monte carlo model checking." In TACAS. Springer-Verlag Berlin, Heidelberg, 2005:271-286.
+[9] Yong Li, Andrea Turrini, Xuechao Sun and Lijun Zhang. "Proving Non-inclusion of Büchi Automata Based on Monte Carlo Sampling." In ATVA. Springer, 2020: 467-483.
-[9] Yong Li, Yu-Fang Chen, Lijun Zhang, and Depeng Liu. "A Novel Learning Algorithm for Büchi Automata based on Family of DFAs and Classification Trees." To appear. {{ :LDBA.pdf |preprint}} (Added an algorithm to transform an FDFA to a limit-deterministic Büchi automaton)
+[10] Yong Li, Yu-Fang Chen, Lijun Zhang, and Depeng Liu. "A Novel Learning Algorithm for Büchi Automata based on Family of DFAs and Classification Trees." To appear in I&C. {{ :LDBA.pdf |preprint}} (Added an algorithm to transform an FDFA to a limit-deterministic Büchi automaton)