Описание: The Handbook provides a comprehensive overview of the concepts, methodologies, and applications being undertaken today in computational linguistics and natural language processing.
Автор: Tiziana Calamoneri; Irene Finocchi; Guiseppe F. It Название: Algorithms and Complexity ISBN: 354034375X ISBN-13(EAN): 9783540343752 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Covers refereed proceedings of the 6th Italian Conference on Algorithms and Computation, CIAC 2006. This title includes 33 revised full papers together with 3 invited papers which address such topics as sequential, parallel and distributed algorithms, data structures, approximation algorithms, randomized algorithms, and, on-line algorithms.
Автор: Brian Castellani; Frederic William Hafferty Название: Sociology and Complexity Science ISBN: 3642100139 ISBN-13(EAN): 9783642100130 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explores the basics and the latest in the integration of sociology and complexity science. It offers an array of real-life applications and showcases a new method for studying social complexity called the Social Systems Toolbox.
Описание: The book introduces new ways of using analytic number theory in cryptography and related areas, such as complexity theory and pseudorandom number generation.Cryptographers and number theorists will find this book useful. The former can learn about new number theoretic techniques which have proved to be invaluable cryptographic tools, the latter about new challenging areas of applications of their skills.
An analysis of two heuristic strategies for the development of mechanistic models, illustrated with historical examples from the life sciences.
In Discovering Complexity, William Bechtel and Robert Richardson examine two heuristics that guided the development of mechanistic models in the life sciences: decomposition and localization. Drawing on historical cases from disciplines including cell biology, cognitive neuroscience, and genetics, they identify a number of "choice points" that life scientists confront in developing mechanistic explanations and show how different choices result in divergent explanatory models. Describing decomposition as the attempt to differentiate functional and structural components of a system and localization as the assignment of responsibility for specific functions to specific structures, Bechtel and Richardson examine the usefulness of these heuristics as well as their fallibility -- the sometimes false assumption underlying them that nature is significantly decomposable and hierarchically organized.
When Discovering Complexity was originally published in 1993, few philosophers of science perceived the centrality of seeking mechanisms to explain phenomena in biology, relying instead on the model of nomological explanation advanced by the logical positivists (a model Bechtel and Richardson found to be utterly inapplicable to the examples from the life sciences in their study). Since then, mechanism and mechanistic explanation have become widely discussed. In a substantive new introduction to this MIT Press edition of their book, Bechtel and Richardson examine both philosophical and scientific developments in research on mechanistic models since 1993.
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