Item type | Current location | Call number | Status | Date due | Barcode |
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Books | 005.131 DAL (Browse shelf) | Available | 034447 |
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005.1309 BER History of programming languages | 005.131 ABA Theory of objects | 005.131 AND Logic programming : operational semantics and proof theory | 005.131 DAL Grammatical inference : learning automata and grammars | 005.131 FLE Formal models of computation : the ultimate limits of computing | 005.131 GON Mathematical logic through Python | 005.131 GRU Parsing techniques : a practical guide |
Includes bibliographical references and index.
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.
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