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Author: Jerzy W. Grzymala-Busse
Publisher: Springer Science & Business Media
ISBN: 146153982X
Category : Computers
Languages : en
Pages : 242
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Book Description
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.
Author: Jerzy W. Grzymala-Busse
Publisher: Springer Science & Business Media
ISBN: 146153982X
Category : Computers
Languages : en
Pages : 242
Get Book Here
Book Description
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.
Author: Jerzy W. Grzymala-Busse
Publisher: Springer Science & Business Media
ISBN: 9780792391692
Category : Computers
Languages : en
Pages : 258
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Book Description
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.
Author: David C. Knue
Publisher:
ISBN:
Category : Expert systems (Computer science)
Languages : en
Pages : 109
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Book Description
A study of using probability to manage uncertainty in expert systems is presented. The study begins with a comprehensive summary of the literature on applying numeric techniques to manage uncertainty in expert systems. In addition to probability, fuzzy sets, certainty factors, and belief functions are addressed. basic principles and rules of information combination for each technique are discussed. The Lindley scoring rule argument for why probability is mathematically techniques is reviewed. The issues why using probability is considered to be a hindrance to managing uncertainty in expert systems are also reviewed. A simple expert system is developed using a state of the art expert system building tool called ALTERID. ALTERID is unique in that it unifies logical and probabilistic inference. This simple expert system is used to explore how probability theory can be used to manage the uncertainty in expert systems. The simple ALTERID based expert system is also used to evaluate the aforementioned issues for using probability to manage uncertainty in expert systems. Keywords: artificial intelligence Bayes theorem; decision analysis; theses.
Author: Jerzy W Grzymala-Busse
Publisher:
ISBN: 9781461539834
Category :
Languages : en
Pages : 248
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Book Description
Author: David C. Knue (CAPT, USAF.)
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages :
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Book Description
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: Enrique Castillo
Publisher: Springer Science & Business Media
ISBN: 1461222702
Category : Computers
Languages : en
Pages : 612
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Book Description
Artificial intelligence and expert systems have seen a great deal of research in recent years, much of which has been devoted to methods for incorporating uncertainty into models. This book is devoted to providing a thorough and up-to-date survey of this field for researchers and students.
Author: George J Klir
Publisher: World Scientific
ISBN: 9814499811
Category : Computers
Languages : en
Pages : 842
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Book Description
This book consists of selected papers written by the founder of fuzzy set theory, Lotfi A Zadeh. Since Zadeh is not only the founder of this field, but has also been the principal contributor to its development over the last 30 years, the papers contain virtually all the major ideas in fuzzy set theory, fuzzy logic, and fuzzy systems in their historical context. Many of the ideas presented in the papers are still open to further development. The book is thus an important resource for anyone interested in the areas of fuzzy set theory, fuzzy logic, and fuzzy systems, as well as their applications. Moreover, the book is also intended to play a useful role in higher education, as a rich source of supplementary reading in relevant courses and seminars.The book contains a bibliography of all papers published by Zadeh in the period 1949-1995. It also contains an introduction that traces the development of Zadeh's ideas pertaining to fuzzy sets, fuzzy logic, and fuzzy systems via his papers. The ideas range from his 1965 seminal idea of the concept of a fuzzy set to ideas reflecting his current interest in computing with words — a computing in which linguistic expressions are used in place of numbers.Places in the papers, where each idea is presented can easily be found by the reader via the Subject Index.
Author: Ian Graham
Publisher: Chapman & Hall
ISBN:
Category : Computers
Languages : en
Pages : 394
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Book Description
A review of the present state of knowledge engineering, drawing together underlying theory from related disciplines, with particular attention to fuzzy logics, the theory of fuzzy sets, and decision support systems, along with practical applications. For managers wishing to evaluate expert decision systems, for systems designers and knowledge engineers, and for advanced undergraduate and graduate students in computer science. Many charts, diagrams, tables, and logical or mathematical formulas; extensive references. Annotation copyrighted by Book News, Inc., Portland, OR
Author: Nouran M. Radwan
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 10
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Book Description
The notion of uncertainty in expert systems is dealing with vague data, incomplete information, and imprecise knowledge. Different uncertainty types which are imprecision, vagueness, ambiguity, and inconsistence need different handling models. Uncertain knowledge representation and analysis is an essential issue.
