Readings in Uncertain Reasoning PDF Download

Author: Glenn Shafer
Publisher: Morgan Kaufmann Publishers
ISBN:
Category : Computers
Languages : en
Pages : 788

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Computing Methodologies -- Artificial Intelligence.

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: Judea Pearl
Publisher: Elsevier
ISBN: 0080514898
Category : Computers
Languages : en
Pages : 573

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Book Description
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information. Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.

Author: John F. Sowa
Publisher: Morgan Kaufmann
ISBN: 1483221148
Category : Computers
Languages : en
Pages : 595

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Book Description
Principles of Semantic Networks: Explorations in the Representation of Knowledge provides information pertinent to the theory and applications of semantic networks. This book deals with issues in knowledge representation, which discusses theoretical topics independent of particular implementations. Organized into three parts encompassing 19 chapters, this book begins with an overview of semantic network structure for representing knowledge as a pattern of interconnected nodes and arcs. This text then analyzes the concepts of subsumption and taxonomy and synthesizes a framework that integrates many previous approaches and goes beyond them to provide an account of abstract and partially defines concepts. Other chapters consider formal analyses, which treat the methods of reasoning with semantic networks and their computational complexity. This book discusses as well encoding linguistic knowledge. The final chapter deals with a formal approach to knowledge representation that builds on ideas originating outside the artificial intelligence literature in research on foundations for programming languages. This book is a valuable resource for mathematicians.

Author: Salem Benferhat
Publisher: Springer
ISBN: 3540446524
Category : Computers
Languages : en
Pages : 832

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Book Description
This book constitutes the refereed proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2001, held in Toulouse, France in September 2001. The 68 revised full papers presented together with three invited papers were carefully reviewed and selected from over a hundred submissions. The book offers topical sections on decision theory, partially observable Markov decision processes, decision-making, coherent probabilities, Bayesian networks, learning causal networks, graphical representation of uncertainty, imprecise probabilities, belief functions, fuzzy sets and rough sets, possibility theory, merging, belief revision and preferences, inconsistency handling, default logic, logic programming, etc.

Author: V.S. Alagar
Publisher: Springer Science & Business Media
ISBN: 1447132424
Category : Computers
Languages : en
Pages : 245

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Book Description
The Software Engineering and Knowledgebase Systems (SOFfEKS) Research Group of the Department of Computer Science, Concordia University, Canada, organized a workshop on Incompleteness and Uncertainty in Information Systems from October 8-9, 1993 in Montreal. A major aim of the workshop was to bring together researchers who share a concern for issues of incompleteness and uncertainty. The workshop attracted people doing fundamental research and industry oriented research in databases, software engineering and AI from North America, Europe and Asia. The workshop program featured six invited talks and twenty other presentations. The invited speakers were: Martin Feather (University of Southern CalifornialInformation Systems Institute) Laks V. S. Lakshmanan (Concordia University) Ewa Orlowska (Polish Academy of Sciences) z. Pawlak (Warsaw Technical University and Academy of Sciences) F. Sadri (Concordia University) A. Skowron (Warsaw University) The papers can be classified into four groups: rough sets and logic, concept analysis, databases and information retrieval, and software engineering. The workshop opened with a warm welcome speech from Dr. Dan Taddeo, Dean, Faculty of Engineering and Computer Science. The first day's presentations were in rough sets, databases and information retrieval. Papers given on the second day centered around software engineering and concept analysis. Sufficient time was given in between presentations to promote active interactions and numerous lively discussions. At the end of two days, the participants expressed their hope that this workshop would be continued.

Author: Bernhard Nebel
Publisher: Morgan Kaufmann Publishers
ISBN:
Category : Computers
Languages : en
Pages : 834

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Book Description
Stringently reviewed papers presented at the October 1992 meeting held in Cambridge, Mass., address such topics as nonmonotonic logic; taxonomic logic; specialized algorithms for temporal, spatial, and numerical reasoning; and knowledge representation issues in planning, diagnosis, and natural langu

Author: Jose Mira
Publisher: Springer Science & Business Media
ISBN: 9783540645825
Category : Business & Economics
Languages : en
Pages : 920

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Book Description
This two-volume set constitutes the refereed proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE-98, held in Benicassim, Castellon, Spain, in June 1998.The two volumes present a total of 187 revised full papers selected from 291 submissions. In accordance with the conference, the books are devoted to new methodologies, knowledge modeling and hybrid techniques. The papers explore applications from virtually all subareas of AI including knowledge-based systems, fuzzyness and uncertainty, formal reasoning, neural information processing, multiagent systems, perception, robotics, natural language processing, machine learning, supervision and control systems, etc..

Author: Ronald Brachman
Publisher: Elsevier
ISBN: 008048932X
Category : Computers
Languages : en
Pages : 413

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Book Description
Knowledge representation is at the very core of a radical idea for understanding intelligence. Instead of trying to understand or build brains from the bottom up, its goal is to understand and build intelligent behavior from the top down, putting the focus on what an agent needs to know in order to behave intelligently, how this knowledge can be represented symbolically, and how automated reasoning procedures can make this knowledge available as needed. This landmark text takes the central concepts of knowledge representation developed over the last 50 years and illustrates them in a lucid and compelling way. Each of the various styles of representation is presented in a simple and intuitive form, and the basics of reasoning with that representation are explained in detail. This approach gives readers a solid foundation for understanding the more advanced work found in the research literature. The presentation is clear enough to be accessible to a broad audience, including researchers and practitioners in database management, information retrieval, and object-oriented systems as well as artificial intelligence. This book provides the foundation in knowledge representation and reasoning that every AI practitioner needs. - Authors are well-recognized experts in the field who have applied the techniques to real-world problems - Presents the core ideas of KR&R in a simple straight forward approach, independent of the quirks of research systems - Offers the first true synthesis of the field in over a decade

Author: Dov M. Gabbay
Publisher: Springer Science & Business Media
ISBN: 9401717370
Category : Mathematics
Languages : en
Pages : 518

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Book Description
Reasoning under uncertainty is always based on a specified language or for malism, including its particular syntax and semantics, but also on its associated inference mechanism. In the present volume of the handbook the last aspect, the algorithmic aspects of uncertainty calculi are presented. Theory has suffi ciently advanced to unfold some generally applicable fundamental structures and methods. On the other hand, particular features of specific formalisms and ap proaches to uncertainty of course still influence strongly the computational meth ods to be used. Both general as well as specific methods are included in this volume. Broadly speaking, symbolic or logical approaches to uncertainty and nu merical approaches are often distinguished. Although this distinction is somewhat misleading, it is used as a means to structure the present volume. This is even to some degree reflected in the two first chapters, which treat fundamental, general methods of computation in systems designed to represent uncertainty. It has been noted early by Shenoy and Shafer, that computations in different domains have an underlying common structure. Essentially pieces of knowledge or information are to be combined together and then focused on some particular question or domain. This can be captured in an algebraic structure called valuation algebra which is described in the first chapter. Here the basic operations of combination and focus ing (marginalization) of knowledge and information is modeled abstractly subject to simple axioms.