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.
|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|
|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|