Handling Uncertainty In Artificial Intelligence
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Handling Uncertainty In Artificial Intelligence
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Author : Jyotismita Chaki
language : en
Publisher: Springer Nature
Release Date : 2023-08-06
Handling Uncertainty In Artificial Intelligence written by Jyotismita Chaki and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-06 with Technology & Engineering categories.
This book demonstrates different methods (as well as real-life examples) of handling uncertainty like probability and Bayesian theory, Dempster-Shafer theory, certainty factor and evidential reasoning, fuzzy logic-based approach, utility theory and expected utility theory. At the end, highlights will be on the use of these methods which can help to make decisions under uncertain situations. This book assists scholars and students who might like to learn about this area as well as others who may have begun without a formal presentation. The book is comprehensive, but it prohibits unnecessary mathematics.
Representing Uncertain Knowledge
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Author : Paul Krause
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Representing Uncertain Knowledge written by Paul Krause and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
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.
Managing Uncertainty In Expert Systems
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Author : Jerzy W. Grzymala-Busse
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Managing Uncertainty In Expert Systems written by Jerzy W. Grzymala-Busse and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
3. Textbook for a course in expert systems,if an emphasis is placed on Chapters 1 to 3 and on a selection of material from Chapters 4 to 7. There is also the option of using an additional commercially available sheU for a programming project. In assigning a programming project, the instructor may use any part of a great variety of books covering many subjects, such as car repair. Instructions for mostofthe "weekend mechanic" books are close stylisticaUy to expert system rules. Contents Chapter 1 gives an introduction to the subject matter; it briefly presents basic concepts, history, and some perspectives ofexpert systems. Then itpresents the architecture of an expert system and explains the stages of building an expert system. The concept of uncertainty in expert systems and the necessity of deal ing with the phenomenon are then presented. The chapter ends with the descrip tion of taxonomy ofexpert systems. Chapter 2 focuses on knowledge representation. Four basic ways to repre sent knowledge in expert systems are presented: first-order logic, production sys tems, semantic nets, and frames. Chapter 3 contains material about knowledge acquisition. Among machine learning techniques, a methodofrule learning from examples is explained in de tail. Then problems ofrule-base verification are discussed. In particular, both consistency and completeness oftherule base are presented.
A Methodology For Uncertainty In Knowledge Based Systems
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Author : Kurt Weichselberger
language : en
Publisher: Lecture Notes in Artificial Intelligence
Release Date : 1990-03-07
A Methodology For Uncertainty In Knowledge Based Systems written by Kurt Weichselberger and has been published by Lecture Notes in Artificial Intelligence this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990-03-07 with Computers categories.
In this book the consequent use of probability theory is proposed for handling uncertainty in expert systems. It is shown that methods violating this suggestion may have dangerous consequences (e.g., the Dempster-Shafer rule and the method used in MYCIN). The necessity of some requirements for a correct combining of uncertain information in expert systems is demonstrated and suitable rules are provided. The possibility is taken into account that interval estimates are given instead of exact information about probabilities. For combining information containing interval estimates rules are provided which are useful in many cases.
Uncertain Information Processing In Expert Systems
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Author : Petr Hajek
language : en
Publisher: CRC Press
Release Date : 1992-06-29
Uncertain Information Processing In Expert Systems written by Petr Hajek and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-06-29 with Computers categories.
Uncertain Information Processing in Expert Systems systematically and critically examines probabilistic and rule-based (compositional, MYCIN-like) systems, the two most important families of expert systems dealing with uncertainty. The book features a detailed introduction to probabilistic systems (including methods using graphical models and methods of knowledge integration), an analysis of compositional systems based on algebraic considerations, an application of graphical models, and the Dempster-Shafer theory of evidence and its use in expert systems. The book will be useful to anyone working in artificial intelligence, statistical computing, symbolic logic, and expert systems.
Uncertainty Handling And Quality Assessment In Data Mining
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Author : Michalis Vazirgiannis
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-07-24
Uncertainty Handling And Quality Assessment In Data Mining written by Michalis Vazirgiannis and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-07-24 with Business & Economics categories.
Uncertainty Handling and Quality Assessment in Data Mining provides an introduction to the application of these concepts in Knowledge Discovery and Data Mining. It reviews the state-of-the-art in uncertainty handling and discusses a framework for unveiling and handling uncertainty. Coverage of quality assessment begins with an introduction to cluster analysis and a comparison of the methods and approaches that may be used. The techniques and algorithms involved in other essential data mining tasks, such as classification and extraction of association rules, are also discussed together with a review of the quality criteria and techniques for evaluating the data mining results. This book presents a general framework for assessing quality and handling uncertainty which is based on tested concepts and theories. This framework forms the basis of an implementation tool, 'Uminer' which is introduced to the reader for the first time. This tool supports the key data mining tasks while enhancing the traditional processes for handling uncertainty and assessing quality. Aimed at IT professionals involved with data mining and knowledge discovery, the work is supported with case studies from epidemiology and telecommunications that illustrate how the tool works in 'real world' data mining projects. The book would also be of interest to final year undergraduates or post-graduate students looking at: databases, algorithms, artificial intelligence and information systems particularly with regard to uncertainty and quality assessment.
The Metaphysical Nature Of The Non Adequacy Claim
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Author : Carlotta Piscopo
language : en
Publisher: Springer
Release Date : 2013-02-01
The Metaphysical Nature Of The Non Adequacy Claim written by Carlotta Piscopo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-01 with Technology & Engineering categories.
Over the last two decades, the field of artificial intelligence has experienced a separation into two schools that hold opposite opinions on how uncertainty should be treated. This separation is the result of a debate that began at the end of the 1960’s when AI first faced the problem of building machines required to make decisions and act in the real world. This debate witnessed the contraposition between the mainstream school, which relied on probability for handling uncertainty, and an alternative school, which criticized the adequacy of probability in AI applications and developed alternative formalisms. The debate has focused on the technical aspects of the criticisms raised against probability while neglecting an important element of contrast. This element is of an epistemological nature, and is therefore exquisitely philosophical. In this book, the historical context in which the debate on probability developed is presented and the key components of the technical criticisms therein are illustrated. By referring to the original texts, the epistemological element that has been neglected in the debate is analyzed in detail. Through a philosophical analysis of the epistemological element it is argued that this element is metaphysical in Popper’s sense. It is shown that this element cannot be tested nor possibly disproved on the basis of experience and is therefore extra-scientific. Ii is established that a philosophical analysis is now compelling in order to both solve the problematic division that characterizes the uncertainty field and to secure the foundations of the field itself.
Uncertainty And Intelligent Information Systems
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Author :
language : en
Publisher:
Release Date :
Uncertainty And Intelligent Information Systems written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Information Processing And Management Of Uncertainty In Knowledge Based Systems Theory And Foundations
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Author : Jesús Medina
language : en
Publisher: Springer
Release Date : 2018-05-30
Information Processing And Management Of Uncertainty In Knowledge Based Systems Theory And Foundations written by Jesús Medina and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-30 with Computers categories.
This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).
Fuzzy Logic For The Management Of Uncertainty
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Author : Lotfi Asker Zadeh
language : en
Publisher: Wiley-Interscience
Release Date : 1992-07-30
Fuzzy Logic For The Management Of Uncertainty written by Lotfi Asker Zadeh and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-07-30 with Computers categories.
Fuzzy Logic for the Management of Uncertainty covers many important topics, including:" "Developments in mathematics that have paved the road for fuzzy logic;" "Deep, and of a broad perspective, exposition of virtually all approaches used in contemporary science for the representation and handling of imperfect (uncertain, imprecise, vague, ambiguous, etc.) information;" "Coverage of practically all relevant and promising directions and approaches in fuzzy logic research including LT--fuzzy logic, model theoretic approaches, intuitionistic fuzzy logic, nonmonotonic fuzzy logic, modifier fuzzy logic;" "VLSI fuzzy logic-based chips that have triggered the implementation of fuzzy logic in so many fields of science and technology;" "A broad coverage of fuzzy logic in approximate reasoning, including basic issues related to the role of fuzzy logic for approximate reasoning, analyses of various definitions of fuzzy implication that is a crucial element in fuzzy logic-based reasoning schemes,