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...

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Bibliographische Detailangaben

1. Verfasser:	De la Higuera, Colin (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Cambridge Cambridge University Press 2010
Schlagworte:	Formal languages Logic, Symbolic and mathematical Maschinelles Lernen Formale Grammatik Inferenz > Künstliche Intelligenz
Online-Zugang:	BSB01 FHN01 URL des Erstveröffentlichers
Zusammenfassung:	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
Beschreibung:	Title from publisher's bibliographic system (viewed on 01 Feb 2016)
Beschreibung:	1 online resource (xiv, 417 pages)
ISBN:	9781139194655
DOI:	10.1017/CBO9781139194655