UID:
almahu_9948233957102882
Format:
1 online resource (xiv, 417 pages) :
,
digital, PDF file(s).
ISBN:
9781139194655 (ebook)
Content:
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 detail: strings and their topology, automata and grammars, whether probabilistic or not. Part II carefully explores the main questions in the field: 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.
Note:
Title from publisher's bibliographic system (viewed on 01 Feb 2016).
Additional Edition:
Print version: ISBN 9780521763165
Language:
English
Subjects:
Computer Science
,
Comparative Studies. Non-European Languages/Literatures
URL:
https://doi.org/10.1017/CBO9781139194655
URL:
https://doi.org/10.1017/CBO9781139194655
URL:
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