Fuzziness and approximate reasoning epistemics on uncertainty, expectation and risk in rational behavior by K. K. Dompere

Cover of: Fuzziness and approximate reasoning | K. K. Dompere

Published by Springer in Berlin .

Written in English

Read online

Subjects:

  • Epistemics,
  • Fuzzy logic,
  • Reasoning,
  • Uncertainty,
  • Risk

Edition Notes

Includes bibliographical references (p. [171]-280) and index.

Book details

StatementKofi Kissi Dompere.
SeriesStudies in fuzziness and soft computing -- v. 237
Classifications
LC ClassificationsB820.3 .D66 2009
The Physical Object
Paginationxxiv, 289 p. :
Number of Pages289
ID Numbers
Open LibraryOL23961700M
ISBN 109783540880868, 9783540880875
LC Control Number2008935497

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This process is formulated as a compositional rule of inference which subsumes modus ponens as a special case. A characteristic feature of approximate reasoning is the fuzziness and nonuniqueness of consequents of fuzzy premisses.

Then syntactic aspects of approximate reasoning are surveyed and the algebraic underpinnings of fuzzy consequence relations are presented and explained.

The second part of the book is devoted to inductive and neuro-fuzzy methods for learning fuzzy rules. It also contains new material on the application of possibility theory to data fusion. This book gathers cutting-edge papers in the area of Computational Intelligence, presented by specialists, and covering all major trends in the research community in order to provide readers with a rich pr.

Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications. Fuzziness in measurement and approximate reasoning is presented as an alternative for dealing with the vague, conflicting, and not definitive decisions in medicine and health care. Conditional restrictions work as a fuzziness mechanism of measure concerning the possibility an evidence can occur.

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fuzzy logics and inference, and consideration of implication suggests Lukasiewicz infinite-valued logic as a base logic for fuzzy reasoning. The paradoxes of the barber, and of sorites, are then analysed to illustrate fuzzy reasoning in action and lead naturally to Zadeh's theory of linguistic hedges and truth.

About this book Fuzzy Implications (FIs) generalize the classical implication and play a similar important role in Fuzzy Logic (FL), both in FL_n and FL_w in the sense of Zadeh. Their importance in applications of FL, viz., Approximate Reasoning (AR), Decision Support Systems, Fuzzy Control (FC), etc., is.

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approximate reasoning Fuzzy Sets and Systems 2 () North-Holland Publishing Company A NEW APPROACH TO APPROXIMATE REASONING USING A FUZZY LOGIC J.F. BALDWIN Department o [ Engineering Mathematic.s, University of Bristol, U.K.

Received February Revised May An approach to approximate reasoning based upon fuzzy logic is given. @book{, author = {Kerre, Etienne}, language = {eng}, title = {Fuzzy sets and approximate reasoning. Xian Jiaotong University Press. Fuzziness and Approximate Reasoning: Epistemics on Uncertainty, Expectation and Risk in Rational Behavior, Hardcover by Dompere, Kofi Kissi, ISBNISBNBrand New, Free shipping in the US Presents the structure and epistemic analysis of uncertainty, expectations and risk in decision-choice actions through the characteristics of substitution.

‎This book offers an inspiring and naïve view on language and reasoning. It presents a new approach to ordinary reasoning that follows the author’s former work on fuzzy logic. Starting from a pragmatic scientific view on meaning as a quantity, and the common sense reasoning from a primitive notion of.

Fuzzy Logic & Approximate Reasoning 6 History, State of the Art, and Future Development Seminal Paper “Fuzzy Logic” by Prof. Lotfi Zadeh, Faculty in Electrical Engineering, U.C.

Berkeley, Sets the Foundation of the “Fuzzy Set Theory” First Application of Fuzzy Logic in Control Engineering (Europe) Introduction of Fuzzy. Making use of different frameworks of approximate reasoning and reasoning under uncertainty, notably probabilistic and fuzzy set-based techniques, this book.

Approximate reasoning is the computational modelling of any part of the process used by humans to reason about natural phenomena or to solve real world problems. The scope of this book includes fuzzy sets, Dempster-Shafer theory, multi-valued logic, probability, random sets, and rough set, near set and hybrid intelligent Rating: % positive.

Fuzziness and Approximate Reasoning: Epistemics on Uncertainty, Expectation and Risk in Rational Behavior (Studies in Fuzziness and Soft Computing Book ) Kindle Edition. $ Fuzzy Preference Ordering of Interval Numbers in Decision Problems (Studies in Fuzziness and Soft Computing Book ).

Chapter 5 Approximate Reasoning Introduction Different fuzzy set-based and possibility theory-based methods have been developed for various types of approximate reasoning. Reasoning with vague predicates, reasoning from imprecise and uncertain pieces of k n o w l e d g e, and reasoning with fuzzy quantifiers.

Approximate Reasoning by Parts Book Review: The monograph offers a view on Rough Mereology, a tool for reasoning under uncertainty, which goes back to Mereology, formulated in terms of parts by Lesniewski, and borrows from Fuzzy Set Theory and Rough Set Theory ideas of.

Probability of a Fuzzy Event as a Fuzzy Set Possibility vs. Probability Part II: Applications of Fuzzy Set Theory 9 Fuzzy Logic and Approximate Reasoning Linguistic Variables Fuzzy Logic Classical Logics Revisited Linguistic Truth Tables Approximate and Plausible Reasoning 9.

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The book provides an introduction to basic concepts as well as some recent advancements in fuzzy set theory, approximate reasoning, artificial neural networks and clustering methods. These methodologies create together the so-called soft computing, which is part of a.

fuzzy logic was established in order to deal with those fuzzy propositions and to underlie approximate reasoning. We have calculated the fuzzy truth values and compare the results of di erent operations (conjunction, disjunction etc) with the approach to Baldwin’s () and with the help of modus ponens law (If p!q and p0then q0.).

• In fuzzy logic, exact reasoning is viewed as a limiting case of approximate reasoning. • In fuzzy logic, everything is a matter of degree. • In fuzzy logic, knowledge is interpreted a collection of elastic or, equivalently, fuzzy The book is organized as follows.

It begins, in chapter 2 ’Fuzzy Sets and Fuzzy. Fuzzy set theory resembles human reasoning in its use of approximate information and uncertainty to generate decisions. It was specifically designed to mathematically represent uncertainty and vagueness. It provides formalized tools for dealing with problems that have imprecise knowledge.

Knowledge can be expressed in a more natural way by using fuzzy sets. Fuzzy Sets In Approximate Reasoning And Information Systems The Handbooks Of Fuzzy Sets Uploaded By Mickey Spillane, approximate reasoning is a key motivation in fuzzy sets and possibility theory this volume provides a coherent view of this field and its impact on database research and information retrieval first the semantic.

Fuzzy techniques in the form of approximate reasoning provide decision support and expert sys-tems with powerful reasoning capabilities. The permissiveness of fuzziness in the human thought process suggests that much of the logic behind thought processing is not traditional two.

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CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Approximate Reasoning is the process Ill " processes by which a possible imprecise conclusion is deduced from a collection of imprecise premises.

Fuzzy logic plays the major role in approximate reasoning. It has the ability to deal with different types of uncertainty. Part Two is devoted to applications of fuzzy set theory and fuzzy logic, including: various methods for constructing membership functions of fuzzy sets; the use of fuzzy logic for approximate reasoning in expert systems; fuzzy systems and controllers; fuzzy databases; fuzzy decision making; and engineering applications.

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