Artificial Intelligence & Expert Systems Sourcebook

320 Pages·1986·6.96 MB·English

by  V. Daniel Hunt (auth.)

Artificial Intelligence &
Expert Systems Sourcebook
OTHER OUTSTANDING VOLUMES IN THE CHAPMAN AND HALL
ADVANCED INDUSTRIAL TECHNOLOGY SERIES
V. Daniel Hunt: SMART ROBOTS: A Handbook of Intelligent Robotic
Systems
Robert I. King: HANDBOOK OF HIGH SPEED MACHINING TECHNOLOGY
David F. Tver and Roger W. Bolz: ENCYCLOPEDIC DICTIONARY OF
INDUSTRIAL TECHNOLOGY: Materials, Processes and Equipment
Roger W. Bolz: MANUFACTURING AUTOMATION MANAGEMENT: A
Productivity Handbook
Igor Aleksander: ARTIFICIAL VISION FOR ROBOTS
D. J. Todd: WALKING MACHINES: An Introduction to Legged Robots
Igor Aleksander: COMPUTING TECHNIQUES FOR ROBOTS
Robert I. King and Robert S. Hahn: HANDBOOK OF MODERN GRINDING
TECHNOLOGY
Douglas M. Considine and Glenn D. Considine: STANDARD HANDBOOK
OF INDUSTRIAL AUTOMATION
Artificial Intelligence &
Expert Systems
Sourcebook
v.
DANIEL HUNT
President
Technology Research Corporation
CHAPMAN & HAll
New York London
This book was prepared as an account of work sponsored by Chapman and Hall.
Neither Chapman and Hall nor Technology Research Corporation nor any of its
employees nor any of their contractors, subcontractors, consultants, or their em
ployees make any warranty, expressed or implied, or assume any legal liability or
responsibility for the accuracy, completeness or usefulness of any information, ap
paratus, product or process disclosed, or represents that its use would not infringe on
privately owned rights.
The views, opinions, and conclusions in this book are those of the author and do not
necessarily represent those of the United States Government.
Public domain information and those documents abstracted or used in full, edited, or
otherwise used are noted in the acknowledgements or on specific pages or illustrations.
First published 1986
by Chapman and Hall
29 West 35th Street, New York, N.Y. 10001
Published in Great Britain by
Chapman and Hall ltd
11 New Fetter lane, london EC4P 4EE
© 1986 Chapman and Hall
Softcover reprint of the hardcover 1st edition 1986
All Rights Reserved. No part of this book may be
reprinted or reproduced or utilized in any form or
by any electronic, mechanical, or other means, now
known or hereafter invented, including photocopying
and recording, or in any information storage or
retrieval system, without permission in writing from
the publishers.
Library of Congress Cataloging in Publication Data
Hunt, V. Daniel.
Artificial Intelligence and Expert Systems Sourcebook
Bibliography: p.
Includes index.
1. Artificial Intelligence Dictionary
2. Expert Systems Dictionary I. Title.
TJ2 1986
ISBN-13: 978-1-4612-9388-0 e-ISBN-13: 978-1-4613-2261-0
DOl: 10.1007/978-1-4613-2261-0
Dedication
To Audrey N. Hunt and Vernon E. Hunt for their continued help and support in
establishing Technology Research Corporation. Both Jan and I appreciate their interest
and participation in projects such as this book.
Table of Contents
PREFACE ......................................................... ix
ACKNOWLEDGMENTS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. xi
INTRODUCTION TO ARTIFICIAL INTELLIGENCE AND
EXPERT SYSTEMS .............................................. 1
DEFINITIONS A TO Z ........................................... 41
POINTS OF CONTACT .......................................... 279
ACRONYMS ................................................... 301
BIBLIOGRAPHy ................................................ 305
TRADEMARKS .................................................. 315
vii
Preface
Artificial Intelligence and expert systems research, development, and demonstration
have rapidly expanded over the past several years; as a result, new terminology is
appearing at a phenomenal rate. This sourcebook provides an introduction to artificial
intelligence and expert systems, it provides brief definitions, it includes brief
descriptions of software products, and vendors, and notes leaders in the field.
Extensive support material is provided by delineating points of contact for receiving
additional information, acronyms, a detailed bibliography, and other reference data.
The terminology includes artificial intelligence and expert system elements for:
• Artificial Intelligence
• Expert Systems
• Natural language Processing
• Smart Robots
• Machine Vision
• Speech Synthesis
The Artificial Intelligence and Expert System Sourcebook is compiled from informa
tion acquired from numerous books, journals, and authorities in the field of artificial
intelligence and expert systems.
I hope this compilation of information will help clarify the terminology for artificial
intelligence and expert systems' activities. Your comments, revisions, or questions are
welcome.
V. Daniel Hunt
Springfield, Virginia
May, 1986
ix
Acknowledgments
The information in Artificial Intelligence and Expert Systems Sourcebook has been
compiled from a wide variety of authorities who are specialists in their respective
fields.
The following publications were used as the basic technical resources for this book.
Portions of these publications may have been used in the book. Those definitions or
artwork used have been reproduced with the permission to reprint of the respective
publisher.
V. Daniel Hunt, Smart Robots, Copyright 1985, Chapman and Hall, New York, N.Y.
Reprinted with permission.
Hayes-Roth, Waterman & levot, Building Expert Systems, Copyright 1983, Addison
Wesley Publishing Company, Reading, Massachusetts. Reprinted with permission.
Donald A. Waterman, A Guide to Expert Systems, Copyright 1985, Addison-Wesley
Publishing Company, Reading, Massachusetts. Reprinted with permission.
Armed Forces Communications and Electronics Association's Professional Develop
ment Center Course 110C entitled "Artificial Intelligence and National Defense:
Applications to Command and Control and Beyond, 1985, AFCEA.
Patrick H. Winston & Berthold Horn, LISP, Copyright 1984, Addison-Wesley, Reading,
Massachusetts. Reprinted with permission.
Patrick H. Winston & Prevdergost, The AI Business: Commercial Uses of Artificial
Intelligence, Copyright 1985, The MIT Press, Cambridge, Massachusetts. Reprinted
with permission.
Paul Harmon and David King, Expert Systems-Artificial Intelligence in Business,
Copyright 1985, John Wiley & Sons, Inc., New York, N.Y. Reprinted with
permission.
Henry C. Mishkoff, Understanding Artificial Intelligence, Copyright 1985, Texas
Instruments Inc. Reprinted with permission.
Industrial Robots-A Summary and Forecast, Copyright 1985, Tech Tran Corporation,
Naperville, Illinois. Reprinted with permission.
Machine Vision Systems-A Summary and Forecast, Copyright 1985, Tech Tran
Corporation, Naperville, Illinois. Reprinted with permission.
Susan J. J. Scown, The Artificial Intelligence Experience: An Introduction, Copyright
1985, Digital Equipment Corporation, Massachusetts. Reprinted with permission.
The preparation of a book of this type is dependent upon an excellent staff, and I
have been fortunate in this regard. Special thanks are extended to Janet c. Hunt,
Audrey and Vernon Hunt, Donald W. Keehan, Kellie-Jo Anne Ackerman, James E.
Wise, Jr., and Carla E. Wise for research assistance. Special thanks to Margaret W.
Alexander for the word processing of the manuscript.
xi
INTRODUCTION TO ARTIFICIAL
INTELLIGENCE AND EXPERT SYSTEMS
Artificial intelligence, also sometimes referred to as machine intelligence or heuristic
programming, is an emerging technology that has recently attracted considerable
publicity. Many applications are now under development. One simple view of the
field is that it is concerned with devising computer programs to make computers
smarter. Thus, research in artificial intelligence is focused on developing computa
tional approaches to intelligent behavior. That effort has 2 goals: making machines
more useful and understanding intelligence.
The computer programs with which artificial intelligence is concerned are primarily
symbolic processes involving complexity, uncertainty, and ambiguity. Those processes
are usually those for which algorithmic solutions do not exist and search is required.
Thus, artificial intelligence deals with the types of problem solving and decision
making that humans continually face in dealing with the world.
This form of problem solving differs markedly from scientific and engineering
calculations that are primarily numeric in nature and for which solutions are known
that produce satisfactory answers. In contrast, artificial intelligence programs deal with
words and concepts and often do not guarantee a correct solution-some wrong
answers being tolerable, as in human problem solving.
Table 1-1 provides a comparison between artificial intelligence and conventional
computer programs. A key characteristic of artificial intelligence programs is "heuristic
search." In complex problems the number of possible solution paths can be
enormous. Thus, artificial intelligence problem solving is usually guided by empirical
rules-rules of thumb-referred to as "heuristics," which help constrain the search.
Table 1-1 Comparison of Artificial Intelligence with Conventional Programming
Artificial Intelligence Conventional Computer Programming
• Primarily symbolic processes • Often primarily numeric
• Heuristic search (solution steps • Algorithmic (solution steps explicit)
implicit)
• Control structure usually separate • Information and control integrated
from domain knowledge together
• Usually easy to modify, update and • Difficult to modify
enlarge
• Some incorrect answers often • Correct answers required
tolerable
• Satisfactory answers usually • Best possible solution usually sought
acceptable
2 • Introduction to Artificial Intelligence
Another aspect of artificial intelligence programs is the extensive use of "domain
knowledge." Intelligence is heavily dependent on knowledge. That knowledge must
be available for use when it is needed during the search. It is common in artificial
intelligence programs to separate such knowledge from the mechanism'that controls
the search. In that way changes in knowledge only require changes in the knowledge
base. In contrast, domain knowledge and control in conventional computer programs
are integrated together. As a result, conventional computer programs are difficult to
modify, as the implications of the changes made in 1 part of the program must be
carefully examined for the impacts and the changes required in other parts of the
program.
The popular view that the study of artificial intelligence is difficult has been partly
due to the awe associated with the notion of intelligence. It has also the result of the
nomenclature used in artificial intelligence and the large size of some of the computer
programs. However, the basic ideas are readily understandable, even though in
complex applications, the "bookkeeping" associated with such programs can be
arduous.
Before we go into details on these basic ideas, it is illuminating to review the history
of artificial intelligence.
THE HISTORY OF ARTIFICIAL INTELLIGENCE
In 1956, 10 scientists convened a conference at Dartmouth College from which
emerged the present field of artificial intelligence. The prediction made by those
scientists was that in 25 years we would all be involved in recreational activities, while
computers would be doing all the work. In 1981 at the International loint Conference
·on Artificial Intelligence in Vancouver, Canada, a panel of 5 of those same scientists
recalled that conference and their overoptimistic forecasts.
In 1956 it was assumed that intelligent behavior was primarily based on smart
reasoning techniques and that bright people could readily devise ad hoc techniques
to produce intelligent computer programs.
Fig. 1-1 lists some of the artificial intelligence activities during the first 15 years. The
major initial activity involved attempts at machine translation. It was thought that
natural language translation could be readily accomplished using a bilingual dictionary
ACTIVITIES
• Attempts at Machine Translation
• ELIZA-Key Word and Template Matching
• Symbolic Integration
• Game Playing-Checkers, Chess
• Pattern Recognition
• Computational logic
• General Problem Solver
LESSONS LEARNED
• Artificial Intelligence Much More Difficult than Expected
• Heuristic Search Required to limit Combinatorial Explosion
• lack of Contextual Knowledge Severely limits Capability
• Expectation Is a Human Characteristic of Intelligence
• Difficult to Handle a Broad Domain (e.g., Common Sense)
Fig. 1-1. A Condensed History of Artificial Intelligence-1965-70