Learning regular sets from queries and counterexamples
Information and Computation
Negative Results for Equivalence Queries
Machine Learning
Journal of Computer and System Sciences
Handbook of formal languages, vol. 1
Introduction To Automata Theory, Languages, And Computation
Introduction To Automata Theory, Languages, And Computation
Machine Learning
Machine Learning
ALT '07 Proceedings of the 18th international conference on Algorithmic Learning Theory
Learning DFA from correction and equivalence queries
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
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In the query learning model, the problem of efficiently identifying a deterministic finite automaton (DFA) has been widely investigated. While DFAs are known to be polynomial time learnable with a combination of membership queries (MQs) and equivalence queries (EQs), each of these types of queries alone are not enough to provide sufficient information for the learner. Therefore, the possibility of having some extra-information shared between the learner and the teacher has been discussed. In this paper, the problem of efficient DFA identification with correction queries (CQs) - an extension of MQs - when additional information is provided to the learner is addressed. We show that knowing the number of states of the target DFA does not help (similar to the case of MQs or EQs), but other parameters such as the reversibility or injectivity degree are useful.