Church-Rosser Thue systems and formal languages
Journal of the ACM (JACM)
Grammatical interface for even linear languages based on control sets
Information Processing Letters
Polynomial Time Learnability of Simple Deterministic Languages
Machine Learning
Learning context-free grammars from structural data in polynomial time
Theoretical Computer Science
Handbook of theoretical computer science (vol. B)
String-rewriting systems
Efficient learning of context-free grammars from positive structural examples
Information and Computation
Handbook of logic in computer science (vol. 2)
The inference of tree languages from finite samples: an algebraic approach
Theoretical Computer Science
Prefix grammars: an alternative characterization of the regular languages
Information Processing Letters
Journal of Computer and System Sciences
Characteristic Sets for Polynomial Grammatical Inference
Machine Learning
Recent advances of grammatical inference
Theoretical Computer Science - Special issue on algorithmic learning theory
A polynomial algorithm testing partial confluence of basic semi-Thue systems
Theoretical Computer Science - Special issue: rewriting systems and applications
Computing the relative entropy between regular tree languages
Information Processing Letters
Inferring pure context-free languages from positive data
Acta Cybernetica
Computing in Systems Described by Equations
Computing in Systems Described by Equations
Efficient Algorithms for the Inference of Minimum Size DFAs
Machine Learning
Stochastic Inference of Regular Tree Languages
Machine Learning
A Version Space Approach to Learning Context-free Grammars
Machine Learning
Learning a Subclass of Context-Free Languages
ICGI '98 Proceedings of the 4th International Colloquium on Grammatical Inference
ICGI '98 Proceedings of the 4th International Colloquium on Grammatical Inference
The EMILE 4.1 Grammar Induction Toolbox
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
Stochastic k-testable Tree Languages and Applications
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
Generalized Stochastic Tree Automata for Multi-relational Data Mining
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
GA-based Learning of Context-Free Grammars using Tabular Representations
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Probabilistic DFA Inference using Kullback-Leibler Divergence and Minimality
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Inference of Context-Free Grammars by Enumeration: Structural Containment as an Ordering Bias
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
Learning Stochastic Regular Grammars by Means of a State Merging Method
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
Regular Grammatical Inference from Positive and Negative Samples by Genetic Search: the GIG Method
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
ALT '01 Proceedings of the 12th International Conference on Algorithmic Learning Theory
Inferring Deterministic Linear Languages
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
Learning Tree Languages from Text
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
Polynomial-time identification of very simple grammars from positive data
Theoretical Computer Science - Selected papers in honour of Setsuo Arikawa
On some families of languages related to the Dyck language
STOC '70 Proceedings of the second annual ACM symposium on Theory of computing
Identifying hierarchical structure in sequences: a linear-time algorithm
Journal of Artificial Intelligence Research
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Termination of single-threaded one-rule semi-thue systems
RTA'05 Proceedings of the 16th international conference on Term Rewriting and Applications
A local search algorithm for grammatical inference
ICGI'10 Proceedings of the 10th international colloquium conference on Grammatical inference: theoretical results and applications
Using Contextual Representations to Efficiently Learn Context-Free Languages
The Journal of Machine Learning Research
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Whereas there is a number of methods and algorithms to learn regular languages, moving up the Chomsky hierarchy is proving to be a challenging task. Indeed, several theoretical barriers make the class of context-free languages hard to learn. To tackle these barriers, we choose to change the way we represent these languages. Among the formalisms that allow the definition of classes of languages, the one of string-rewriting systems (SRS) has outstanding properties. We introduce a new type of SRS's, called Delimited SRS (DSRS), that are expressive enough to define, in a uniform way, a noteworthy and non trivial class of languages that contains all the regular languages, $$\{a^{n}b^{n}: n \geq 0 \}$$, $$\{w\in \{a,b\}^{*}:|w|_{a}=|w|_{b}\}$$, the parenthesis languages of Dyck, the language of Lukasiewicz, and many others. Moreover, DSRS's constitute an efficient (often linear) parsing device for strings, and are thus promising candidates in forthcoming applications of grammatical inference. In this paper, we pioneer the problem of their learnability. We propose a novel and sound algorithm (called LARS) which identifies a large subclass of them in polynomial time (but not data). We illustrate the execution of our algorithm through several examples, discuss the position of the class in the Chomsky hierarchy and finally raise some open questions and research directions.