Learning regular sets from queries and counterexamples
Information and Computation
Negative Results for Equivalence Queries
Machine Learning
Characterizations of monotonic and dual monotonic language learning
Information and Computation
The String-to-String Correction Problem
Journal of the ACM (JACM)
Inference of Reversible Languages
Journal of the ACM (JACM)
Formal language identification: query learning vs. gold-style learning
Information Processing Letters
Learning Balls of Strings with Correction Queries
ECML '07 Proceedings of the 18th European conference on Machine Learning
One-Shot Learners Using Negative Counterexamples and Nearest Positive Examples
ALT '07 Proceedings of the 18th international conference on Algorithmic Learning Theory
ALT '07 Proceedings of the 18th international conference on Algorithmic Learning Theory
A characterization of the language classes learnable with correction queries
TAMC'07 Proceedings of the 4th international conference on Theory and applications of models of computation
Learning regular tree languages from correction and equivalence queries
Journal of Automata, Languages and Combinatorics
Inductive inference and language learning
TAMC'06 Proceedings of the Third international conference on Theory and Applications of Models of Computation
Learning DFA from correction and equivalence queries
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
Generalizing over several learning settings
ICGI'10 Proceedings of the 10th international colloquium conference on Grammatical inference: theoretical results and applications
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The adult-child interaction which takes place during the child's language acquisition process has been the inspiration for Angluin's teacher-learner model [1], the forerunner of today's active learning field. But the initial types of queries have some drawbacks: equivalence queries are both unrealistic and computationally costly; membership queries, on the other hand, are not informative enough, not being able to capture the feedback received by the child when he or she makes mistakes. This is why a new type of query (called correction query), weaker than the first one and more informative than the second, appeared. While in the case of natural languages it is well understood what correcting means, in formal language theory different objects may require different types of corrections. Therefore, several types of correction queries have been introduced so far. In this paper we investigate the relations existing between different models of correction queries, as well as their connection to other well-known Gold-style and query learning models. The study comprises results obtained in the general case when time complexity issues are ignored, and in the restricted case when efficiency constraints are imposed.