Grammatical Inference: Learning Automata and Grammars

by Colin de la Higuera

The problem of inducing, learning or inferring grammars has been studied for decades, but only in recent years has grammatical inference emerged as an independent field with connections to many scientific disciplines, including bio-informatics, computational linguistics and pattern recognition. This book meets the need for a comprehensive and unified summary of the basic techniques and results, suitable for researchers working in these various areas. In Part I, the objects of use for grammatical inference are studied in strings and their topology, automata and grammars, whether probabilistic or not. Part II carefully explores the main questions in the What does learning mean? How can we associate complexity theory with learning? In Part III the author describes a number of techniques and algorithms that allow us to learn from text, from an informant, or through interaction with the environment. These concern automata, grammars, rewriting systems, pattern languages or transducers.

432 pages, Hardcover

First published April 1, 2010

Reviews

[David MacIver · Rating 4 out of 5]

This is a really nice book. It's got a good light overview of a lot of different topics in the subject. It doesn't go as in depth as I'd like into some of the bits I wanted to know more about, but it's got a really good set of references and further readings to follow up when you want to know more, and what is there is generally clear and approachable.