EDP Sciences logo
Subscriber Authentication Point
Search
Menu
All issues RAIRO-Theor. Inf. Appl., 33 1 (1999) 1-19 Article references

Articles citing this article

The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).

Cited article:

Active model learning of stochastic reactive systems (extended version)

Edi Muškardin, Martin Tappler, Bernhard K. Aichernig and Ingo Pill
Software and Systems Modeling 23 (2) 503 (2024)
https://doi.org/10.1007/s10270-024-01158-0

A Framework for Identification and Validation of Affine Hybrid Automata from Input-Output Traces

Xiaodong Yang, Omar Ali Beg, Matthew Kenigsberg and Taylor T. Johnson
ACM Transactions on Cyber-Physical Systems 6 (2) 1 (2022)
https://doi.org/10.1145/3470455

Formal Methods and Software Engineering

Wenjing Chu, Shuo Chen and Marcello Bonsangue
Lecture Notes in Computer Science, Formal Methods and Software Engineering 13478 54 (2022)
https://doi.org/10.1007/978-3-031-17244-1_4

Automatically ‘Verifying’ Discrete-Time Complex Systems through Learning, Abstraction and Refinement

Jingyi Wang, Jun Sun, Shengchao Qin and Cyrille Jegourel
IEEE Transactions on Software Engineering 47 (1) 189 (2021)
https://doi.org/10.1109/TSE.2018.2886898

L∗-based learning of Markov decision processes (extended version)

Martin Tappler, Bernhard K. Aichernig, Giovanni Bacci, Maria Eichlseder and Kim G. Larsen
Formal Aspects of Computing 33 (4-5) 575 (2021)
https://doi.org/10.1007/s00165-021-00536-5

Software Engineering and Formal Methods

Martin Tappler, Edi Muškardin, Bernhard K. Aichernig and Ingo Pill
Lecture Notes in Computer Science, Software Engineering and Formal Methods 13085 481 (2021)
https://doi.org/10.1007/978-3-030-92124-8_27

Formal Methods – The Next 30 Years

Martin Tappler, Bernhard K. Aichernig, Giovanni Bacci, Maria Eichlseder and Kim G. Larsen
Lecture Notes in Computer Science, Formal Methods – The Next 30 Years 11800 651 (2019)
https://doi.org/10.1007/978-3-030-30942-8_38

Learning probabilistic models for model checking: an evolutionary approach and an empirical study

Jingyi Wang, Jun Sun, Qixia Yuan and Jun Pang
International Journal on Software Tools for Technology Transfer 20 (6) 689 (2018)
https://doi.org/10.1007/s10009-018-0492-7

Statistical Relational Learning With Unconventional String Models

Mai H. Vu, Ashkan Zehfroosh, Kristina Strother-Garcia, et al.
Frontiers in Robotics and AI 5 (2018)
https://doi.org/10.3389/frobt.2018.00076

Fundamental Approaches to Software Engineering

Jingyi Wang, Jun Sun, Qixia Yuan and Jun Pang
Lecture Notes in Computer Science, Fundamental Approaches to Software Engineering 10202 3 (2017)
https://doi.org/10.1007/978-3-662-54494-5_1

Grammatical Inference for Computational Linguistics

Synthesis Lectures on Human Language Technologies, Grammatical Inference for Computational Linguistics (2016)
https://doi.org/10.1007/978-3-031-02159-6

Leveraging Applications of Formal Methods, Verification and Validation. Technologies for Mastering Change

André de Matos Pedro, Paul Andrew Crocker and Simão Melo de Sousa
Lecture Notes in Computer Science, Leveraging Applications of Formal Methods, Verification and Validation. Technologies for Mastering Change 7609 508 (2012)
https://doi.org/10.1007/978-3-642-34026-0_38

Links between probabilistic automata and hidden Markov models: probability distributions, learning models and induction algorithms

P. Dupont, F. Denis and Y. Esposito
Pattern Recognition 38 (9) 1349 (2005)
https://doi.org/10.1016/j.patcog.2004.03.020

Probabilistic finite-state machines - part II

E. Vidal, F. Thollard, C. de la Higuera, F. Casacuberta and R.C. Carrasco
IEEE Transactions on Pattern Analysis and Machine Intelligence 27 (7) 1026 (2005)
https://doi.org/10.1109/TPAMI.2005.148

Algorithmic Learning Theory

Omri Guttman, S. V. N. Vishwanathan and Robert C. Williamson
Lecture Notes in Computer Science, Algorithmic Learning Theory 3734 171 (2005)
https://doi.org/10.1007/11564089_15

Probabilistic finite-state machines - part I

E. Vidal, F. Thollard, C. de la Higuera, F. Casacuberta and R.C. Carrasco
IEEE Transactions on Pattern Analysis and Machine Intelligence 27 (7) 1013 (2005)
https://doi.org/10.1109/TPAMI.2005.147

Parsing with probabilistic strictly locally testable tree languages

J.L. Verdu-Mas, R.C. Carrasco and J. Calera-Rubio
IEEE Transactions on Pattern Analysis and Machine Intelligence 27 (7) 1040 (2005)
https://doi.org/10.1109/TPAMI.2005.144

Grammatical Inference: Algorithms and Applications

Franck Thollard and Alexander Clark
Lecture Notes in Computer Science, Grammatical Inference: Algorithms and Applications 3264 248 (2004)
https://doi.org/10.1007/978-3-540-30195-0_22

Grammatical Inference: Algorithms and Applications

Colin de la Higuera and Jose Oncina
Lecture Notes in Computer Science, Grammatical Inference: Algorithms and Applications 3264 175 (2004)
https://doi.org/10.1007/978-3-540-30195-0_16

Grammatical Inference: Algorithms and Applications

Jérôme Callut and Pierre Dupont
Lecture Notes in Computer Science, Grammatical Inference: Algorithms and Applications 3264 77 (2004)
https://doi.org/10.1007/978-3-540-30195-0_8

A language measure for performance evaluation of discrete-event supervisory control systems

Xi Wang and Asok Ray
Applied Mathematical Modelling 28 (9) 817 (2004)
https://doi.org/10.1016/j.apm.2003.12.003

Detecting and extracting named entities from spontaneous speech in a mixed-initiative spoken dialogue context: How May I Help You?sm,tm

Frédéric Béchet, Allen L Gorin, Jeremy H Wright and Dilek Hakkani Tür
Speech Communication 42 (2) 207 (2004)
https://doi.org/10.1016/j.specom.2003.07.003

Predictive Robot Programming: Theoretical and Experimental Analysis

Kevin R. Dixon, John M. Dolan and Pradeep K. Khosla
The International Journal of Robotics Research 23 (9) 955 (2004)
https://doi.org/10.1177/0278364904044401

Multi-Agent Systems and Applications III

Arnaud Mounier, Olivier Boissier and François Jacquenet
Lecture Notes in Computer Science, Multi-Agent Systems and Applications III 2691 158 (2003)
https://doi.org/10.1007/3-540-45023-8_16

Grammatical Inference: Algorithms and Applications

Yann Esposito, Aurélien Lemay, François Denis and Pierre Dupont
Lecture Notes in Computer Science, Grammatical Inference: Algorithms and Applications 2484 77 (2002)
https://doi.org/10.1007/3-540-45790-9_7

Grammatical Inference: Algorithms and Applications

Christopher Kermorvant and Pierre Dupont
Lecture Notes in Computer Science, Grammatical Inference: Algorithms and Applications 2484 149 (2002)
https://doi.org/10.1007/3-540-45790-9_12

FINITE STATE LANGUAGE MODELS SMOOTHED USING n-GRAMS

DAVID LLORENS, JUAN MIGUEL VILAR and FRANCISCO CASACUBERTA
International Journal of Pattern Recognition and Artificial Intelligence 16 (03) 275 (2002)
https://doi.org/10.1142/S0218001402001666

Grammatical Inference: Algorithms and Applications

Pierre Dupont and Juan-Carlos Amengual
Lecture Notes in Computer Science, Grammatical Inference: Algorithms and Applications 1891 51 (2000)
https://doi.org/10.1007/978-3-540-45257-7_5

Grammatical Inference: Algorithms and Applications

Colin de la Higuera and Franck Thollard
Lecture Notes in Computer Science, Grammatical Inference: Algorithms and Applications 1891 141 (2000)
https://doi.org/10.1007/978-3-540-45257-7_12

Grammatical Inference: Algorithms and Applications

Francisco Casacuberta and Colin de la Higuera
Lecture Notes in Computer Science, Grammatical Inference: Algorithms and Applications 1891 15 (2000)
https://doi.org/10.1007/978-3-540-45257-7_2