Author : Stanford University. Computer Science Dept. Knowledge Systems Laboratory
Publisher :
Page : 50 pages
File Size : 44,25 MB
Release : 1989
Category : Expert systems (Computer science)
ISBN :
Author : Thomas R. Gruber
Publisher : Elsevier
Page : 337 pages
File Size : 22,32 MB
Release : 2013-07-10
Category : Technology & Engineering
ISBN : 0323162584
The Acquisition of Strategic Knowledge deals with the automation of the acquisition of strategic knowledge and describes a knowledge acquisition program called ASK, which elicits strategic knowledge from domain experts and puts it in operational form. This book explores the dynamics of intelligent systems and how the components of knowledge systems (including a human expert) interact to produce intelligence. Emphasis is placed on how to represent knowledge that experts require to make decisions about actions. The move toward abstract tasks and how tasks are solved are discussed, along with their implications for knowledge acquisition, particularly the acquisition of expert strategies. This book is comprised of eight chapters and begins with an overview of the knowledge acquisition problem for strategic knowledge, as well as the relevance of strategic knowledge to artificial intelligence. The next chapter describes a dialog session between the ASK knowledge acquisition assistant and the user (""the expert""). The discussion then turns to software architecture with which to represent strategic knowledge; design and implementation of an assistant for acquiring strategic knowledge; and approaches to knowledge acquisition. Two applications of the ASK system are considered: to evaluate the usability of the elicitation technique with real users and to test the adequacy of the strategy rule representation upon which the approach is dependent. The scope of ASK, its sources of power, and its underlying assumptions are also outlined. This monograph will be a valuable resource for knowledge systems designers and those interested in artificial intelligence and expert systems.
Author : Bruce G. Buchanan
Publisher : Morgan Kaufmann Publishers
Page : 926 pages
File Size : 29,27 MB
Release : 1993
Category : Computers
ISBN :
Readings in Knowledge Acquisition and Learning collects the best of the artificial intelligence literature from the fields of machine learning and knowledge acquisition. This book brings together the perspectives on constructing knowledge-based systems from these two historically separate subfields of artificial intelligence.
Author : David A. Klein
Publisher : Psychology Press
Page : 229 pages
File Size : 36,14 MB
Release : 2013-02-01
Category : Psychology
ISBN : 1134768532
This book presents a framework for building intelligent systems based on the mathematical decision models of Decision Analysis. The author provides new techniques for automated explanation and knowledge acquisition in formally sound systems that reason about complex tradeoffs in decisions. Also included are specifications for implementing these techniques in computer programs, along with demonstration applications in marketing, process control, and medicine. Readers with an interest in artificial intelligence will gain a foundation for building formally justifiable, intelligible, modifiable systems for computing decisions involving multiple considerations, with applications across a variety of domains. Beyond decision models, the methodology of the work reported suggests a more general approach to employing formal mathematical models in transparent intelligent systems. Decision-analysis experts will find a collection of methods for explaining decision-analytic advice to clients in intuitive terms, for simplifying parameter assessment, and for managing changing preferences over time. The book provides sufficient background material to promote understanding by readers who may be unfamiliar with artificial intelligence, with decision analysis, or with both fields, and such material is labeled to increase the well-versed reader's efficiency in skipping particular sections.
Author : Sandra Marcus
Publisher : Springer
Page : 288 pages
File Size : 18,68 MB
Release : 2012-04-06
Category : Computers
ISBN : 9781468471243
In June of 1983, our expert systems research group at Carnegie Mellon University began to work actively on automating knowledge acquisition for expert systems. In the last five years, we have developed several tools under the pressure and influence of building expert systems for business and industry. These tools include the five described in chapters 2 through 6 - MORE, MOLE, SALT, KNACK and SIZZLE. One experiment, conducted jointly by developers at Digital Equipment Corporation, the Soar research group at Carnegie Mellon, and members of our group, explored automation of knowledge acquisition and code development for XCON (also known as R1), a production-level expert system for configuring DEC computer systems. This work influenced the development of RIME, a programming methodology developed at Digital which is the subject of chapter 7. This book describes the principles that guided our work, looks in detail at the design and operation of each tool or methodology, and reports some lessons learned from the enterprise. of the work, brought out in the introductory chapter, is A common theme that much power can be gained by understanding the roles that domain knowledge plays in problem solving. Each tool can exploit such an understanding because it focuses on a well defined problem-solving method used by the expert systems it builds. Each tool chapter describes the basic problem-solving method assumed by the tool and the leverage provided by committing to the method.
Author : Sandra Marcus
Publisher : Springer Science & Business Media
Page : 150 pages
File Size : 48,92 MB
Release : 2012-12-06
Category : Computers
ISBN : 146131531X
What follows is a sampler of work in knowledge acquisition. It comprises three technical papers and six guest editorials. The technical papers give an in-depth look at some of the important issues and current approaches in knowledge acquisition. The editorials were pro duced by authors who were basically invited to sound off. I've tried to group and order the contributions somewhat coherently. The following annotations emphasize the connections among the separate pieces. Buchanan's editorial starts on the theme of "Can machine learning offer anything to expert systems?" He emphasizes the practical goals of knowledge acquisition and the challenge of aiming for them. Lenat's editorial briefly describes experience in the development of CYC that straddles both fields. He outlines a two-phase development that relies on an engineering approach early on and aims for a crossover to more automated techniques as the size of the knowledge base increases. Bareiss, Porter, and Murray give the first technical paper. It comes from a laboratory of machine learning researchers who have taken an interest in supporting the development of knowledge bases, with an emphasis on how development changes with the growth of the knowledge base. The paper describes two systems. The first, Protos, adjusts the training it expects and the assistance it provides as its knowledge grows. The second, KI, is a system that helps integrate knowledge into an already very large knowledge base.
Author : Brian R. Gaines
Publisher :
Page : 418 pages
File Size : 43,10 MB
Release : 1990
Category : Computers
ISBN :
This book presents a broad view of the fundamental issues involved in knowledge acquisition and their place in knowledge-based systems development. The book covers theory based methods and problem modeling approaches to provide a strong theoretical and methodological basis for practical and effective knowledge acquisition techniques.
Author : Khaled W. al- Dhaher
Publisher :
Page : 406 pages
File Size : 29,54 MB
Release : 1992
Category : Expert systems (Computer science)
ISBN :
The representation method, strategy schemata, possesses features that are similar to several other representation methodologies. It captures inter-strategy knowledge, such as structural and inheritance relationships that are useful in the acquisition and refinement processes outlined by the paradigm. The nature of these schemata coupled with the reasoning methods explicitly associated with them, differentiate them from other representation and associated reasoning methodologies."
Author : Ray Bareiss
Publisher : Academic Press
Page : 184 pages
File Size : 22,98 MB
Release : 2014-05-10
Category : Computers
ISBN : 1483216373
Exemplar-Based Knowledge Acquisition: A Unified Approach to Concept Representation, Classification, and Learning covers the fundamental issues in cognitive science and the technology for solving real problems. This text contains six chapters and begins with a description of the rationale for the design of Protos Approach, its construction and performance. The succeeding chapters discuss how the Protos approach meets the requirements of representing concepts, using them for classification, and acquiring them from available training. These chapters also deal with the design and implementation of Protos. These topics are followed by a presentation of examples of the application of Protos to audiology and evaluate its performance. The final chapters survey related work in the areas of case-based reasoning and automated knowledge acquisition and the contributions of Protos approach. This book will be of great value to psychologists, psychiatrists, and researchers in the field of artificial intelligence.
Author : Karen L. McGraw
Publisher :
Page : 408 pages
File Size : 20,48 MB
Release : 1989
Category : Computers
ISBN :
This book presents a practical view of the knowledge acquisition process, its methodologies and techniques, in order to enable readers to develop expert systems knowledge bases more effectively. It strikes a balance between presenting (1) summaries of research in the field of knowledge acquisition and (2) methodologies and techniques that have been applied and tested on numerous programs in various contexts. Written for novice knowledge engineers or others tasked with acquiring knowledge for the systematic development of expert systems. The presentation of the material does not presume a background in either computer science or artificial intelligence.
