Expert Systems

Expert Systems
Author: Ian Graham
Publisher: Chapman & Hall
Total Pages: 394
Release: 1988
Genre: Computers
ISBN:

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

Masters Theses in the Pure and Applied Sciences

Masters Theses in the Pure and Applied Sciences
Author: Wade H. Shafer
Publisher: Springer Science & Business Media
Total Pages: 391
Release: 2012-12-06
Genre: Science
ISBN: 1461524539

Masters Theses in the Pure and Applied Sciences was first conceived, published, and disseminated by the Center for Information and Numerical Data Analysis and Synthesis (CINDAS)* at Purdue University in 1957, starting its coverage of theses with the academic year 1955. Beginning with Volume 13, the printing and dis semination phases of the activity were transferred to University Microfilms/Xerox of Ann Arbor, Michigan, with the though that such an arrangement would be more beneficial to the academic and general scientific and technical community. After five years of this joint undertaking we had concluded that it was in the interest of all concerned if the printing and distribution of the volumes were handled by an international publishing house to assure improved service and broader dissemi nation. Hence, starting with Volume 18, Masters Theses in the Pure and Applied Sciences has been disseminated on a worldwide basis by Plenum Publishing Corporation of New York, and in the same year the coverage was broadened to include Canadian universities. All back issues can also be ordered from Plenum. We have reported in Volume 37 (thesis year 1992) a total of 12,549 thesis titles from 25 Canadian and 153 United States universities. We are sure that this broader base for these titles reported will greatly enhance the value of this impor tant annual reference work. While Volume 37 reports theses submitted in 1992, on occasion, certain uni versities do report theses submitted in previous years but not reported at the time.

Representing Uncertain Knowledge

Representing Uncertain Knowledge
Author: Paul Krause
Publisher: Springer Science & Business Media
Total Pages: 287
Release: 2012-12-06
Genre: Computers
ISBN: 9401120846

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.

Uncertainty Management in Information Systems

Uncertainty Management in Information Systems
Author: Amihai Motro
Publisher: Springer Science & Business Media
Total Pages: 473
Release: 2012-12-06
Genre: Computers
ISBN: 1461562457

As its title suggests, "Uncertainty Management in Information Systems" is a book about how information systems can be made to manage information permeated with uncertainty. This subject is at the intersection of two areas of knowledge: information systems is an area that concentrates on the design of practical systems that can store and retrieve information; uncertainty modeling is an area in artificial intelligence concerned with accurate representation of uncertain information and with inference and decision-making under conditions infused with uncertainty. New applications of information systems require stronger capabilities in the area of uncertainty management. Our hope is that lasting interaction between these two areas would facilitate a new generation of information systems that will be capable of servicing these applications. Although there are researchers in information systems who have addressed themselves to issues of uncertainty, as well as researchers in uncertainty modeling who have considered the pragmatic demands and constraints of information systems, to a large extent there has been only limited interaction between these two areas. As the subtitle, "From Needs to Solutions," indicates, this book presents view points of information systems experts on the needs that challenge the uncer tainty capabilities of present information systems, and it provides a forum to researchers in uncertainty modeling to describe models and systems that can address these needs.

Uncertain Information Processing In Expert Systems

Uncertain Information Processing In Expert Systems
Author: Petr Hajek
Publisher: CRC Press
Total Pages: 310
Release: 1992-06-29
Genre: Computers
ISBN: 9780849363689

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.

Systematic Introduction to Expert Systems

Systematic Introduction to Expert Systems
Author: Frank Puppe
Publisher: Springer Science & Business Media
Total Pages: 353
Release: 2012-12-06
Genre: Computers
ISBN: 3642779719

At present one of the main obstacles to a broader application of expert systems is the lack of a theory to tell us which problem-solving methods areavailable for a given problem class. Such a theory could lead to significant progress in the following central aims of the expert system technique: - Evaluating the technical feasibility of expert system projects: This depends on whether there is a suitable problem-solving method, and if possible a corresponding tool, for the given problem class. - Simplifying knowledge acquisition and maintenance: The problem-solving methods provide direct assistance as interpretation models in knowledge acquisition. Also, they make possible the development of problem-specific expert system tools with graphical knowledge acquisition components, which can be used even by experts without programming experience. - Making use of expert systems as a knowledge medium: The structured knowledge in expert systems can be used not only for problem solving but also for knowledge communication and tutorial purposes. With such a theory in mind, this book provides a systematic introduction to expert systems. It describes the basic knowledge representations and the present situation with regard tothe identification, realization, and integration of problem-solving methods for the main problem classes of expert systems: classification (diagnostics), construction, and simulation.

Handbook of Defeasible Reasoning and Uncertainty Management Systems

Handbook of Defeasible Reasoning and Uncertainty Management Systems
Author: Dov M. Gabbay
Publisher: Springer Science & Business Media
Total Pages: 518
Release: 2013-04-17
Genre: Mathematics
ISBN: 9401717370

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.

Analysis and Management of Uncertainty

Analysis and Management of Uncertainty
Author: Bilal M. Ayyub
Publisher:
Total Pages: 458
Release: 1992
Genre: Computers
ISBN:

Topics in this book range from mathematical theories to probabilistic analysis of structures in civil engineering. Mathematical background is first covered including: probabilistic and possibilistic conceptualization of uncertainty, the algebraic structure of conditional reasoning, uncertainty modeling in anticipatory systems, reasoning by hypothesizing causal models, fuzzy sets and truth functionality. The second part deals with expert systems and neuronal structures and includes papers on expert appraisement and counter-appraisement with experton processes, the management of uncertainty, transferable belief models for expert judgement, fuzzy neural expert systems, and inverse dynamic adaptive control. Of particular interest is the last section which deals with applications in engineering. The articles presented here show just how far this field has progressed from theory to practice. They deal with such topics as the prediction of earthquake ground motion and structural responses, bridge ratings, safety and reliability evaluations of transmission lines, and transportation.