Learning regular sets from queries and counterexamples
Information and Computation
Learning context-free grammars from structural data in polynomial time
Theoretical Computer Science
Learnable classes of categorial grammars
Learnable classes of categorial grammars
Stochastic Inference of Regular Tree Languages
Machine Learning
Machine Learning
Machine Learning
Learning Tree Languages from Text
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
Learning a regular tree language from a teacher
DLT'03 Proceedings of the 7th international conference on Developments in language theory
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IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Minimizing deterministic weighted tree automata
Information and Computation
MAT learners for recognizable tree languages and tree series
Acta Cybernetica
Minimal tree language extensions: a keystone of XML type compatibility and evolution
ICTAC'10 Proceedings of the 7th International colloquium conference on Theoretical aspects of computing
ICGI'10 Proceedings of the 10th international colloquium conference on Grammatical inference: theoretical results and applications
Learning of church-Rosser tree rewriting systems
ICGI'10 Proceedings of the 10th international colloquium conference on Grammatical inference: theoretical results and applications
A randomised inference algorithm for regular tree languages
Natural Language Engineering
Inference of residual finite-state tree automata from membership queries and finite positive data
DLT'11 Proceedings of the 15th international conference on Developments in language theory
Distributional learning of simple context-free tree grammars
ALT'11 Proceedings of the 22nd international conference on Algorithmic learning theory
Four one-shot learners for regular tree languages and their polynomial characterizability
Theoretical Computer Science
Conservative type extensions for XML data
Transactions on Large-Scale Data- and Knowledge-centered systems IX
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We investigate regular tree languages' exact learning from positive examples and membership queries. Input data are trees of the language to infer. The learner computes new trees from the inputs and asks the oracle whether or not they belong to the language. From the answers, the learner may ask further membership queries until he finds the correct grammar that generates the target language. This paradigm was introduced by Angluin in the seminal work [D. Angluin, A note on the number of queries needed to identify regular languages, Information and Control 51 (1981) 76-87] for the case of regular word languages. Neither negative examples, equivalence queries nor counter-examples are allowed in this paradigm. We describe an efficient algorithm which is polynomial in the size of the examples for learning the whole class of regular tree languages. The convergence is ensured when the set of examples contains a representative sample of the language to guess. A finite subset of a regular tree language is representative for if every transition of the minimal tree automaton for is used at least once for the derivation of an element of the set .