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Tuesday, July 28, 2020 | History

2 edition of On reasoning with uncertainty and belief change. found in the catalog.

On reasoning with uncertainty and belief change.

Shengli Shi

On reasoning with uncertainty and belief change.

by Shengli Shi

  • 376 Want to read
  • 21 Currently reading

Published by The Author] in [s.l .
Written in English


Edition Notes

Thesis (D. Phil.) - Universityof Ulster, 1995.

ID Numbers
Open LibraryOL19097195M

-- Conditionals and the Ramsey Test -- Logics for Belief Base Updating -- Reasoning about Merged Information -- Numerical Representation of Uncertainty -- Belief Change Rules in Ordinal and Numerical Uncertainty Theories -- Parallel Combination of Information Sources -- Table of Contents to Volume 1 -- Table of Contents to Volume 2.\/span. Qualitative Methods for Reasoning under Uncertainty. By Simon Parsons. Overview. In this book Simon Parsons describes qualitative methods for reasoning under uncertainty, "uncertainty" being a catch-all term for various types of imperfect information. The advantage of qualitative methods is that they do not require precise numerical information.

  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 /5(14). Comprised of 23 chapters, this book begins with a review of situation calculus and a solution to the frame problem, along with the use of a regression method for reasoning about the effect of actions. A novel programming language for high-level robotic control is described, along with a knowledge-based framework for belief change.

Reasoning about Uncertainty by Joseph Y. Halpern Clear, Interesting, Insightful Uncertainty is a fundamental and unavoidable feature of daily life; in order to deal with uncertaintly intelligently, we need to be able to represent it and reason about it. In this book, Joseph Halpern examines formal ways of. In this book Simon Parsons describes qualitative methods for reasoning under uncertainty, "uncertainty" being a catch-all term for various types of imperfect information. The advantage of qualitative methods is that they do not require precise numerical information. Instead, they work with abstractions such as interval values and information about how values change.


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On reasoning with uncertainty and belief change by Shengli Shi Download PDF EPUB FB2

Uncertainty is a fundamental and unavoidable feature of daily life; in order to deal with uncertaintly 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. Reasoning about Uncertainty is a very valuable synthesis of the mathematics of uncertainty as it has developed in a number of related fields -- probability, statistics, computer science, game theory, artificial intelligence, and philosophy.

Researchers in all of these fields will find this a very useful book -- both for its elegant treatment of Cited by: Finally, the book presents the numerical view of belief change, beyond the probabilistic framework, covering such approaches as possibility theory, belief functions and convex gambles.

The work thus presents a unified view of belief change operators, drawing from a widely scattered literature embracing philosophical logic, artificial.

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 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. Note: If you're looking for a free download links of Belief Change (Handbook of Defeasible Reasoning and Uncertainty Management Systems) Pdf, epub, docx and torrent then this site is not for you.

only do ebook promotions online and we does not. Uncertainty is a fundamental and unavoidable feature of daily life; in order to deal with uncertaintly 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/5. Chapter 6 appears earlier than expected. It covers the issues of uncertainty in multiagent systems.

Agents rely heavily on the notion of belief in their knowledge representation. Given that this book is heavily biased toward notions of belief and plausibility in modeling uncertainty, I. The topics include the revision of belief sets and belief bases, logics for updating a belief base, reasoning about merged information, the numerical representation of uncertainty, ordinal and numerical uncertainty theories, and the parallel combination of information sources.

The series has emerged from a study funded by the European Union. Belief change is an emerging field of artificial intelligence and information science dedicated to the dynamics of information and the present book provides a state-of-the-art picture of its formal foundations.

It deals with the addition, deletion and combination of pieces of information and, Handbook of Defeasible Reasoning and Uncertainty.

IEEE Xplore, delivering full text access to the world's highest quality technical literature in engineering and technology. | IEEE Xplore. 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. Uncertainty is a fundamental and unavoidable feature of daily life in order to deal with uncertaintly 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. Abstract. The situation of belief change in numerical uncertainty frameworks differs from the situation in classical logic in two respects: on the one hand, uncertainty theories are tailored to representing epistemic states involving shades of belief and are more expressive than classical logic in that by: Abstract.

Belief networks are a new, potentially important, class of knowledge-based models. ARCO1, currently under development at the Atlantic Richfield Company (ARCO) and the University of Southern California (USC), is the most advanced reported implementation of these models in.

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.

Reasoning About Uncertainty (CS ): belief change, counterfactual reasoning, and problems of statistical inference, particularly that of going from statistical information to degrees of belief. The course follows closely the material in the book Reasoning About Uncertainty, which actually was inspired by early versions of the course.

Introduction and overview -- 2. Representing uncertainty -- 3. Updating beliefs -- 4. Independence and Bayesian networks -- 5. Expectation -- 6. Multi-agent systems -- 7. Logics for reasoning about uncertainty -- 8. Beliefs, defaults, and counterfactuals -- 9.

Belief revision -- First-order modal logic -- From statistics to beliefs -- Belief change is an emerging field of artificial intelligence and information science dedicated to the dynamics of information and the present book provides a state-of-the-art picture of its formal foundations.

It deals with the addition, deletion and combination of pieces of information and, more generally, with the revision, updating and. You can write a book review and share your experiences.

Other readers will always be interested in your opinion of the books you've read. Whether you've loved the book or not, if you give your honest and detailed thoughts then people will find new books that are right for them. Some of the reasons for reasoning under uncertainty: True uncertainty.

E.g., flipping a coin. Theoretical ignorance. There is no complete theory which is known about the problem domain. E.g., medical diagnosis. Laziness. The space of relevant factors is very large, and would require too much work to list the complete set of antecedents and.

This book constitutes the refereed proceedings of the 15th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARUheld in Belgrade, Serbia, in September The conference provided a forum for discussing the theoretical aspects of reasoning about knowledge and tackled topics ranging from the logic of iterated belief revision and backwards forward induction to information acquisition from multi-agent resources, infinitely epistemic logic, and coherent belief revision in .This book constitutes the refereed proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU Coverage in the 78 revised full papers, presented together with three invited papers, includes Bayesian networks, graphical models, Price: $