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Author: Simon Parsons
Publisher: MIT Press
ISBN: 9780262161688
Category : Computers
Languages : en
Pages : 534
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Book Description
Using qualitative methods to deal with imperfect information.
Author: Simon Parsons
Publisher: MIT Press
ISBN: 9780262161688
Category : Computers
Languages : en
Pages : 534
Get Book Here
Book Description
Using qualitative methods to deal with imperfect information.
Author: Xinde Li
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 12
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Book Description
In this paper, we present a new 2-tuple linguistic representation model, i.e. Distribution Function Model (DFM), for combining imprecise qualitativeinformation using fusion rules drawn from Dezert-Smarandache Theory (DSmT) framework.
Author: Christos Frangos
Publisher: Christos Frangos
ISBN: 9609873901
Category : Business & Economics
Languages : en
Pages : 595
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Book Description
Author:
Publisher: IOS Press
ISBN:
Category :
Languages : en
Pages : 6097
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Book Description
Author: Joseph Y. Halpern
Publisher: MIT Press
ISBN: 0262533804
Category : Computers
Languages : en
Pages : 505
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Book Description
Formal ways of representing uncertainty and various logics for reasoning about it; updated with new material on weighted probability measures, complexity-theoretic considerations, and other topics. In order to deal with uncertainty intelligently, we need to be able to represent it and reason about it. In this book, Joseph Halpern examines formal ways of representing uncertainty and considers various logics for reasoning about it. While the ideas presented are formalized in terms of definitions and theorems, the emphasis is on the philosophy of representing and reasoning about uncertainty. Halpern surveys possible formal systems for representing uncertainty, including probability measures, possibility measures, and plausibility measures; considers the updating of beliefs based on changing information and the relation to Bayes' theorem; and discusses qualitative, quantitative, and plausibilistic Bayesian networks. This second edition has been updated to reflect Halpern's recent research. New material includes a consideration of weighted probability measures and how they can be used in decision making; analyses of the Doomsday argument and the Sleeping Beauty problem; modeling games with imperfect recall using the runs-and-systems approach; a discussion of complexity-theoretic considerations; the application of first-order conditional logic to security. Reasoning about Uncertainty is accessible and relevant to researchers and students in many fields, including computer science, artificial intelligence, economics (particularly game theory), mathematics, philosophy, and statistics.
Author: David Heckerman
Publisher: Morgan Kaufmann
ISBN: 1483214516
Category : Computers
Languages : en
Pages : 554
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Book Description
Uncertainty in Artificial Intelligence contains the proceedings of the Ninth Conference on Uncertainty in Artificial Intelligence held at the Catholic University of America in Washington, DC, on July 9-11, 1993. The papers focus on methods of reasoning and decision making under uncertainty as applied to problems in artificial intelligence (AI) and cover topics ranging from knowledge acquisition and automated model construction to learning, planning, temporal reasoning, and machine vision. Comprised of 66 chapters, this book begins with a discussion on causality in Bayesian belief networks before turning to a decision theoretic account of conditional ought statements that rectifies glaring deficiencies in classical deontic logic and forms a sound basis for qualitative decision theory. Subsequent chapters explore trade-offs in constructing and evaluating temporal influence diagrams; normative engineering risk management systems; additive belief-network models; and sensitivity analysis for probability assessments in Bayesian networks. Automated model construction and learning as well as algorithms for inference and decision making are also considered. This monograph will be of interest to both students and practitioners in the fields of AI and computer science.
Author: Paul Krause
Publisher: Springer Science & Business Media
ISBN: 9401120846
Category : Computers
Languages : en
Pages : 287
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Book Description
The representation of uncertainty is a central issue in Artificial Intelligence (AI) and is being addressed in many different ways. Each approach has its proponents, and each has had its detractors. However, there is now an in creasing move towards the belief that an eclectic approach is required to represent and reason under the many facets of uncertainty. We believe that the time is ripe for a wide ranging, yet accessible, survey of the main for malisms. In this book, we offer a broad perspective on uncertainty and approach es to managing uncertainty. Rather than provide a daunting mass of techni cal detail, we have focused on the foundations and intuitions behind the various schools. The aim has been to present in one volume an overview of the major issues and decisions to be made in representing uncertain knowl edge. We identify the central role of managing uncertainty to AI and Expert Systems, and provide a comprehensive introduction to the different aspects of uncertainty. We then describe the rationales, advantages and limitations of the major approaches that have been taken, using illustrative examples. The book ends with a review of the lessons learned and current research di rections in the field. The intended readership will include researchers and practitioners in volved in the design and implementation of Decision Support Systems, Ex pert Systems, other Knowledge-Based Systems and in Cognitive Science.
Author: Bernadette Bouchon-Meunier
Publisher: Springer Science & Business Media
ISBN: 9783540601166
Category : Computers
Languages : en
Pages : 648
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Book Description
This book presents a topical selection of full refereed research papers presented during the 5th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU '94, held in Paris, France in July 1994. The topical focus is on the role of uncertainty in the contruction of intelligent computing systems and it is shown how the concepts of AI, neural networks, and fuzzy logic can be utilized for that purpose. In total, there are presented 63 thoroughly revised papers organized in sections on fundamental issues; theory of evidence; networks, probabilistic, statistical, and informational methods; possibility theory, logics, chaos, reusability, and applications.
Author: Kerstin Fink
Publisher: Springer Science & Business Media
ISBN: 3322812405
Category : Business & Economics
Languages : en
Pages : 285
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Book Description
Kerstin Fink discusses the two mainstream measurement fields: the cognitive science approach and the management approach. She develops the knowledge potential view which is determined by nine key measurement variables, i.e. content, culture, networking, organizational knowledge, learning and training, customer and competitor knowledge, and knowledge management systems.
Author: Simon Parsons
Publisher: Mit Press
ISBN: 9780262528740
Category :
Languages : en
Pages : 528
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Book Description
Using qualitative methods to deal with imperfect information.
