Decision Processes in Dynamic Probabilistic Systems, A.V. Gheorghe
Автор: Koller Daphne, Friedman Nir Название: Probabilistic Graphical Models: Principles and Techniques ISBN: 0262013193 ISBN-13(EAN): 9780262013192 Издательство: MIT Press Рейтинг: Цена: 21161.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions.
Most tasks require a person or an automated system to reason -- to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.
Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.
Автор: Bass Название: Probabilistic Techniques in Analysis ISBN: 0387943870 ISBN-13(EAN): 9780387943879 Издательство: Springer Рейтинг: Цена: 12012.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Exploring the use of techniques drawn from probability research to tackle problems in mathematical analysis, this study includes discussion of the construction of the Martin boundary, Dahlberg`s Theorem, probabilistic proofs of the boundary Harnack principle, and much more.
Автор: Pierre Bessi?re; Christian Laugier; Roland Siegwar Название: Probabilistic Reasoning and Decision Making in Sensory-Motor Systems ISBN: 3642097847 ISBN-13(EAN): 9783642097843 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The chapters contain a sizable segment of cognitive systems research in Europe. Contributions come from leading academic institutions within the European projects Bayesian Inspired Brain and Artifact (BIBA) and Bayesian Approach to Cognitive Systems (BACS).
Описание: This book proposes the formulation of an efficient methodology that estimates energy system uncertainty and predicts Remaining Useful Life (RUL) accurately with significantly reduced RUL prediction uncertainty.
Автор: Annabelle McIver; Charles Carroll Morgan Название: Abstraction, Refinement and Proof for Probabilistic Systems ISBN: 1441923128 ISBN-13(EAN): 9781441923127 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Illustrates by example the typical steps necessary in computer science to build a mathematical model of any programming paradigm .
Presents results of a large and integrated body of research in the area of `quantitative` program logics.
Автор: Tim Bedford Название: Probabilistic Risk Analysis ISBN: 0521773202 ISBN-13(EAN): 9780521773201 Издательство: Cambridge Academ Рейтинг: Цена: 14731.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Drawing on extensive experience, the authors focus on the conceptual and mathematical foundations underlying the quantification, interpretation and management of risk. They cover standard topics as well as important new subjects such as the use of expert judgement and uncertainty propagation. The relationship with decision making is highlighted.
Автор: A.V. Gheorghe Название: Decision Processes in Dynamic Probabilistic Systems ISBN: 9401067082 ISBN-13(EAN): 9789401067089 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In the literature of decision analysis it is traditional to rely on the tools provided by probability theory to deal with problems in which uncertainty plays a substantive role. , n, in which X and Yare real-valued variables and Ai and Bi are fuzzy numbers exemplified by small, large, not very small, close to 5, etc.
Автор: Guillermo L. G?mez M. Название: Dynamic Probabilistic Models and Social Structure ISBN: 9401051143 ISBN-13(EAN): 9789401051149 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this way classical analytical mechanics was able to establish some general results, gaining insight through explicit solution of some simple cases and developing various methods of approximation for handling more complicated ones.
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