Learning regular sets from queries and counterexamples
Information and Computation
Random DFA's can be approximately learned from sparse uniform examples
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Learning non-deterministic finite automata from queries and counterexamples
Machine intelligence 13
Characteristic Sets for Polynomial Grammatical Inference
Machine Learning
Handbook of formal languages, vol. 1
Derivatives of Regular Expressions
Journal of the ACM (JACM)
Introduction To Automata Theory, Languages, And Computation
Introduction To Automata Theory, Languages, And Computation
ICGI '98 Proceedings of the 4th International Colloquium on Grammatical Inference
Efficient Ambiguity Detection in C-NFA, a Step Towards the Inference on Non Deterministic Automata
ICGI '00 Proceedings of the 5th International Colloquium on Grammatical Inference: Algorithms and Applications
Learning Regular Languages Using Non Deterministic Finite Automata
ICGI '00 Proceedings of the 5th International Colloquium on Grammatical Inference: Algorithms and Applications
Some Classes of Regular Languages Identifiable in the Limit from Positive Data
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
Residual Finite State Automata
Fundamenta Informaticae
Identification of biRFSA languages
Theoretical Computer Science - In honour of Professor Christian Choffrut on the occasion of his 60th birthday
From dirt to shovels: fully automatic tool generation from ad hoc data
Proceedings of the 35th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
On the efficient construction of quasi-reversible automata for reversible languages
Information Processing Letters
Learning Regular Languages Using Nondeterministic Finite Automata
CIAA '08 Proceedings of the 13th international conference on Implementation and Applications of Automata
Learning Languages from Bounded Resources: The Case of the DFA and the Balls of Strings
ICGI '08 Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications
Universal automata and NFA learning
Theoretical Computer Science
On Rational Stochastic Languages
Fundamenta Informaticae
Regular expression learning for information extraction
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
On locally reversible languages
Theoretical Computer Science
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
A context-free markup language for semi-structured text
PLDI '10 Proceedings of the 2010 ACM SIGPLAN conference on Programming language design and implementation
ICGI'10 Proceedings of the 10th international colloquium conference on Grammatical inference: theoretical results and applications
On the use of non-deterministic automata for presburger arithmetic
CONCUR'10 Proceedings of the 21st international conference on Concurrency theory
Using Contextual Representations to Efficiently Learn Context-Free Languages
The Journal of Machine Learning Research
Towards dual approaches for learning context-free grammars based on syntactic concept lattices
DLT'11 Proceedings of the 15th international conference on Developments in language theory
Inference improvement by enlarging the training set while learning DFAs
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
A family of algorithms for non deterministic regular languages inference
CIAA'06 Proceedings of the 11th international conference on Implementation and Application of Automata
A merging states algorithm for inference of RFSAs
ICGI'06 Proceedings of the 8th international conference on Grammatical Inference: algorithms and applications
Is learning RFSAs better than learning DFAs?
CIAA'05 Proceedings of the 10th international conference on Implementation and Application of Automata
Polynomial characteristic sets for DFA identification
Theoretical Computer Science
On Rational Stochastic Languages
Fundamenta Informaticae
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Residual languages are important and natural components of regular languages and several grammatical inference algorithms naturally rely on this notion. In order to identify a given target language L, classical inference algorithms try to identify words which define identical residual languages of L. Here, we study whether it could be interesting to perform a tighter analysis by identifying inclusion relations between the residual languages of L. We consider the class of Residual Finite State Automata (RFSAs). An RFSA A is a NonDeterministic Automaton whose states corresponds to residual languages of the language LA it recognizes. The inclusion relations between residual languages of LA can be naturally materialized on A. We prove that the class of RFSAs is not polynomially characterizable. We lead some experiments which show that when a regular language is randomly drawn by using a nondeterministic representation, the number of inclusion relations between its residual languages is very important. Moreover, its minimal RFSA representation is much smaller than its minimal DFA representation. Finally, we design a new learning algorithm, DeLeTe2, based on the search for the inclusion relations between the residual languages of the target language. We give sufficient conditions for the identifiability of the target language. We experimentally compare the performance of DeLeTe2 to those of classical inference algorithms.