Table Of ContentThe Handbook of Artificial Intelligence
Volume I
Edited by
Avron Barr
and
Edward A. Feigenbaum
Department of Computer Science
Stanford University
HEURISTECH PRESS WILLIAM KAUFMANN, INC.
Stanford, California Los Altos, California
Library of Congress Cataloging in Publication Data:
The handbook of artificial intelligence.
Bibliography: p. 363
Includes index.
I. Artificial intelligence. I. Barr, Avron, 1949-
II. Feigenbaum, Edward A.
Q335.H36 001.53'5 80-28621
ISBN 0-86576-004-7 (set)
ISBN 0-86576-005-5 (Vol. 1)
ISBN 0-86576-088-8 (set) (pbk.)
ISBN 0-86576-089-6 (Vol. I) (pbk.)
Copyright © 1981 by William Kaufmann, Inc.
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write to: Permissions, William Kaufmann, Inc., 95 First Street,
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10 9 8 7 6
Printed in the United States of America
To the graduate students
LIST OF CONTRIBUTORS
The following people have made the Handbook a reality. Together, over
the last five years, they have combed the entire literature of AI and
have attempted to make a coherent presentation of this very diverse
field. These researchers and students, from Stanford and other AI
centers, have contributed to Volumes I and Π or are now engaged in
preparing Volume ΙΠ (being edited by Paul R. Cohen).
Chapter Editors
Janice Aikins Robert Elschlager
James S. Bennett Lawrence Fagan
Victor Ciesielski (Rutgers U) Anne v.d.L. Gardner
William J. Clancey Takeo Kanade (CMU)
Paul R. Cohen Jorge Phillips
James E. Davidson Steve Tappel
Thomas Dietterich Stephen Westfold
Contributors
Robert Anderson (Rand) Jon Doyle
Douglas Appelt R. Geoff Dromey (U Wollongong)
David Arnold Richard Duda (Fairchild)
Michael Ballantyne (U Texas) Robert Engelmore
David Barstow (Schlumberger) Ramez El-Masri (Honeywell)
Peter Biesel (Rutgers U) Susan Epstein (Rutgers U)
Lee Blaine (IMSSS) Robert Filman (Indiana U)
W. W. Bledsoe (U Texas) Fritz Fisher
Rodney Brooks Christian Freksa (UC Berkeley)
Bruce Buchanan Peter Friedland
Richard Chestek Richard Gabriel
Kenneth Clarkson Michael Genesereth
Randall Davis (MIT) Neil Goldman (ISI)
Gerard Dechen Ira Goldstein (Xerox)
Johan de Kleer (Xerox) George Heidorn (IBM)
X List of Contributors
Douglas Hofstadter (Indiana William Scherlis (CMU)
Elaine Kant (CMU) Andrew Silverman
William Laaser (Xerox) Donald Smith (Rutgers U)
Douglas Lenat Phillip Smith (U Waterloo)
William Long (MIT) Reid G. Smith (Canadian DREA)
Robert London William Swartout (MIT)
Pamela McCorduck William van Meile
Robert Moore (SRI) Richard Waldinger (SRI)
Richard Pattis Richard Waters (MIT)
Neil C. Rowe Sholom Weiss (Rutgers U)
Gregory Ruth (MIT) David Wilkins (SRI)
Daniel Sagalowicz (SRI) Terry Winograd
Behrokh Samadi
Reviewers
Harold Abelson (MIT) Jonathan King
Saul Amarel (Rutgers U) Casimir Kulikowski (Rutgers U)
Robert Balzer (ISI) Brian P. McCune (AI&DS)
Harry Barrow (Fairchild) Donald Michie (U Edinburgh)
Thomas Binford Nils Nilsson (SRI)
Daniel Bobrow (Xerox) Glen Ouchi (UC Santa Cruz)
John Seely Brown (Xerox) Ira Pohl (UC Santa Cruz)
Richard Burton (Xerox) Herbert Simon (CMU)
Lewis Creary David E. Smith
Andrea diSessa (MIT) Dennis Smith
Daniel Dolata (UC Santa Cruz) Mark Steflk (Xerox)
Lee Erman (ISI) Albert Stevens (BBN)
Adele Goldberg (Xerox) Allan Terry
Cordell Green (SCI) Perry Thorndyke (Rand)
Norman Haas (SRI) Donald Walker (SRI)
Kenneth Kahn (MIT) Keith Wescourt (Rand)
Production
Lester Ernest Roy Nordblom
Marion Hazen Thomas Rindfleisch
David Fuchs Ellen Smith
Dianne Kanerva Helen Tognetti
PREFACE
ARTIFICIAL INTELLIGENCE is of growing interdisciplinary interest and
practical importance. People with widely varying backgrounds and pro-
fessions are discovering new ideas and new tools in this young science.
Theory-minded psychologists have developed new models of the mind
based on the fundamental concepts of AI—symbol systems and infor-
mation processing. Linguists are also interested in these basic notions,
as well as in AI work in computational linguistics, aimed at producing
programs that actually understand language. And philosophers, in
considering the progress, problems, and potential of this work toward
nonhuman intelligence, have sometimes found new perspectives on the
age-old problems of the nature of mind and knowledge.
In other spheres of activity, people often first come across AI in the
form of some "expert" system that is being applied experimentally in
their own area—chemical data interpretation, symbolic integration,
infectious disease diagnosis, DNA sequencing, computer systems debug-
ging, structural engineering, computer-chip design, and so on. As the
cost of computation continues to fall, many new computer applications
become viable. Since, for many of these, there are no mathematical
"cores" to structure the calculational use of the computer, such areas
will inevitably be served by symbolic models and symbolic inference
techniques. Yet those who understand symbolic computation have been
speaking largely to themselves for the first 25 years of ATs history. We
feel that it is urgent for AI to "go public" in the manner intended by
this three-volume Handbook of Artificial Intelligence.
Xll Preface
Since the Handbook project began in 1975, dozens of researchers
have labored to produce short, jargon-free explanations of AI pro-
gramming techniques and concepts. With these volumes, we have tried
to build bridges to be crossed by engineers, by professionals and
scientists in other fields, and by our own colleagues in computer science.
We have tried to cover the breadth and depth of AI, presenting general
overviews of the scientific issues, as well as detailed discussions of
particular techniques and exemplary computer systems. And, most
important, we have presented the key concepts—search, divide-and-
conquer, semantic nets, means-ends analysis, hierarchical planning, ATNs,
procedural knowledge, blackboard architecture, scripts and frames, goal-
directed and data-driven processing, learning, and many more—in the
context of their actual application in AI. If they were presented more
abstractly, the unique perspective afforded by AI research on these
universal ideas would be lost. Throughout, we have tried to keep in
mind the reader who is not a specialist in AI.
In short, we have tried to present a survey of AÎ research that is
motivated historically and scientifically, without attempting to present a
new synthesis of this young, multifaceted, rapidly changing field. One
can view these Handbook volumes as an encyclopedia of AI programming
techniques, their successful applications, some of their limitations, and
the computational concepts that have been used to describe them.
Readers from different fields will interpret these data in different
ways—we hope that many of you will find useful new ideas and new
perspectives.
The Handbook contains several different kinds of articles. Key AI
concepts and techniques are described in core articles (e.g., heuristic
search, semantic nets). Important individual AI programs (e.g., SHRDLU,
MACSYMA, PROSPECTOR) are presented in separate articles that indi-
cate, among other things, the designer's goals, the techniques employed,
and the reasons why the program is important. The problems and
approaches in each major area are discussed in overview articles, which
should be particularly useful to those who seek a summary of the
underlying issues that motivate AI research.
We intend that the Handbook of Artificial Intelligence be a living
and changing reference work. In particular, we hope that our colleagues
will take time to alert us to errors we have made, of omission or
commission, and that we have an opportunity to correct these in future
editions.
Preface xiu
Acknowledgments
Many people have contributed to the Handbook project. On pages
ix-x is an alphabetical list of those who have been involved so far,
including article contributors, reviewers, and the chapter editors who
have spent months working the individual chapters into coherent pre-
sentations of a particular AI subarea. The following is as accurate a
reconstruction as possible of the contributions to this first volume over
the last five years.
The "Search" chapter was written by Anne Gardner, starting from
some articles prepared for a problem seminar in the spring of 1975.
Background material was made available by Nils Nilsson, who also read
earlier drafts, as did Bruce Buchanan, Lewis Creary, James Davidson,
Ira Pohl, Reid Smith, Mark Stefik, and David Wilkins.
"Representation of Knowledge" was edited by Avron Barr and James
Davidson. The article on logic was written by Robert Filman, semantic
nets by Douglas Appelt, semantic primitives by Anne Gardner, and
frames by James Bennett. Mark Stefik carefully reviewed an early draft
of this chapter.
Anne Gardner, James Davidson, and Avron Barr edited "Under-
standing Natural Language." Articles were worked on by Janice Aikins,
Rodney Brooks, William Clancey, Paul Cohen, Gerard Dechen, Richard
Gabriel, Norman Haas, Douglas Hofstadter, Andrew Silverman, Phillip
Smith, Reid Smith, William van Meile, and David Wilkins. Neil Gold-
man reviewed an early draft of the chapter. Terry Winograd made
background material available and also reviewed an early draft.
"Understanding Spoken Language" was prepared by Lawrence Fagan,
Paul Cohen, and Avron Barr, with helpful comments from James Ben-
nett, Lee Erman, and Donald Walker.
The professional editor responsible for the form of the final copy,
including electronic typesetting and page design, was Dianne Kanerva.
Earlier in the project's history, professional editing on several chapters
was done by Helen Tognetti. Ellen Smith also assisted in this impor-
tant work.
The book was set in Computer Modern fonts (Knuth, 1979) and was
produced directly on a computer-driven phototypesetting device. Pub-
lisher William Kaufmann and his staff have been patient and helpful
throughout this process.
XIV Preface
The Advanced Research Projects Agency of the Department of De-
fense and the Biotechnology Resources Program of the National Insti-
tutes of Health supported the Handbook project as part of their long-
standing and continuing efforts to develop and disseminate the science
and technology of AI. Earlier versions of Handbook material were
distributed as technical reports of the Stanford Computer Science
Department. The electronic text-preparation facilities available to Stan-
ford computer scientists on the SAIL, SCORE, and SUMEX computers
were used.
We wish specially to acknowledge Anne Gardner, whose scholarship
during the early years of the Handbook project was invaluable, and
inspirational.
Finally, let us not forget that many of the programs described
herein as landmark events in the history of AI were labored over single-
handedly by graduate students trying to implement their thesis ideas.
These AI systems have consistently been among the most complex and
innovative computer programs of their day. They stand as a tribute to
the caliber and creativity of those who have been drawn to AI research.
Chapter I
Introduction
