The course called "Grammatical Inference" is part of the curriculum of the second year ATAL speciality of the Computer Science Masters at the University of Nantes.

A lot of material corresponding to this course can be found on the web with slides and videos corresponding to tutorials given at summer schools or conferences. This is a good starting point.

The book is also a reference.

A number of algorithms have been transformed into software. In several cases, this software can be downloaded here.

>># | Date | Lecture | References | Slides |
---|---|---|---|---|

1 | 11/9/2013 | An introduction to grammatical inference. About what learning a language means, how we can measure success | Chapter 2 | Slides |

2 | 18/9/2013 | An introduction to grammatical inference. A motivating example | Chapter 1, Videolectures | Slides |

3 | 25/9/2013 | Learning: identifying or approximating? | Chapter 6 | Homework |

4 | 2/10/2013 | Learning from text | Chapter 8 | Slides |

5 | 9/10/2013 | Learning from text: the window languages | Chapter 11 | Same slides as lecture 4 |

6 | 16/10/2013 | Homework | ||

7 | 23/10/2013 | Learning from an informant: the RPNI algorithm and variants | Chapter 12 | Slides |

8 | 6/11/2013 | Active learning 1 | Chapter 9 | Slides |

9 | 14/11/2013 | Active learning 2 | Chapter 13 | See videolectures, Angluin's paper |

10 | 20/11/2013 | Active learning 1 | Chapter 9 | |

11 | 27/11/2013 | Learning distributions: why? How should we measure success? About distances between distributions, learning the weights given a structure. EM, Gibbs sampling and the spectral methods | Chapter 5, Chapter 17 | Slides |

12 | 2/12/2013 | Learning distributions: state merging techniques | Chapter 16 | |

13 | 11/12/2013 | Learning probabilistic transducers | Not in the book | Article |

14 | 18/12/2013 | Exam |