Logical Structures for Representation of Knowledge and Uncertainty, Ellen Hisdal
Автор: Dov M. Gabbay; Philippe Smets Название: Quantified Representation of Uncertainty and Imprecision ISBN: 9048150388 ISBN-13(EAN): 9789048150380 Издательство: Springer Рейтинг: Цена: 41647.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This Handbook was produced in the style of previous handbook series like the Handbook of Philosoph- ical Logic, the Handbook of Logic in Computer Science, the Handbook of Logic in Artificial Intelligence and Logic Programming, and can be seen as a companion to them in covering the wide applications of logic and reasoning.
Описание: The book offers a comprehensive and timely overview of advanced mathematical tools for both uncertainty analysis and modeling of parallel processes, with a special emphasis on intuitionistic fuzzy sets and generalized nets.
Автор: Jim Cogdell; Ju-Lee Kim; Chen-Bo Zhu Название: Representation Theory, Number Theory, and Invariant Theory ISBN: 3319597272 ISBN-13(EAN): 9783319597270 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book contains selected papers based on talks given at the "Representation Theory, Number Theory, and Invariant Theory" conference held at Yale University from June 1 to June 5, 2015.
Описание: The purpose of the book is to advance in the understanding of brain function by defining a general framework for representation based on category theory. The idea is to bring this mathematical formalism into the domain of neural representation of physical spaces, setting the basis for a theory of mental representation, able to relate empirical findings, uniting them into a sound theoretical corpus. The innovative approach presented in the book provides a horizon of interdisciplinary collaboration that aims to set up a common agenda that synthesizes mathematical formalization and empirical procedures in a systemic way. Category theory has been successfully applied to qualitative analysis, mainly in theoretical computer science to deal with programming language semantics. Nevertheless, the potential of category theoretic tools for quantitative analysis of networks has not been tackled so far. Statistical methods to investigate graph structure typically rely on network parameters. Category theory can be seen as an abstraction of graph theory. Thus, new categorical properties can be added into network analysis and graph theoretic constructs can be accordingly extended in more fundamental basis. By generalizing networks using category theory we can address questions and elaborate answers in a more fundamental way without waiving graph theoretic tools. The vital issue is to establish a new framework for quantitative analysis of networks using the theory of categories, in which computational neuroscientists and network theorists may tackle in more efficient ways the dynamics of brain cognitive networks. The intended audience of the book is researchers who wish to explore the validity of mathematical principles in the understanding of cognitive systems. All the actors in cognitive science: philosophers, engineers, neurobiologists, cognitive psychologists, computer scientists etc. are akin to discover along its pages new unforeseen connections through the development of concepts and formal theories described in the book. Practitioners of both pure and applied mathematics e.g., network theorists, will be delighted with the mapping of abstract mathematical concepts in the terra incognita of cognition.
Описание: The M logic goes an important step further than the BP logic in that it can distinguish between certain types of information supply sentences which have the same representation in the BP logic as well as in traditional first order logic, although they clearly have different meanings (see example 6.
Автор: Bernadette Bouchon-Meunier; Ronald R. Yager; Lotfi Название: Uncertainty in Knowledge Bases ISBN: 3540543465 ISBN-13(EAN): 9783540543466 Издательство: Springer Рейтинг: Цена: 16070.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Contains papers which reflect research in the field of the management and processing of uncertain information, foundations of the various approaches, attempts to develop systems combining approaches, and some paradigmatic domains of intelligent systems.
Описание: This book explains the first published consistency proof of PA. A notable aspect of the proof is the representation of ordinal numbers that was developed by Gentzen. The topic should interest researchers and students who work on proof theory, history of proof theory or Hilbert`s program and who do not mind reading mathematical texts.ГЇВїВЅ
Описание: Part III comprises the more detailed arguments about Carroll`s reasoning, and Part IV contains reprints of rare original material on proportional representation by Carroll, James Garth Marshall, and Walter Baily.
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