Rule-Based Programming

316 Pages·1996·12.078 MB·English

by  Thaddeus J. Kowalski, Leon S. Levy (auth.), Thaddeus J. Kowalski, Leon S. Levy (eds.)

RULE-BASED PROGRAMMING
AlIaT
THE KLUWER INTERNATIONAL SERIES
IN ENGINEERING AND COMPUTER SCIENCE
KNOWLEDGE REPRESENTATION, LEARNING
AND EXPERT SYSTEMS
Consulting Editor
Tom Mitchell
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GENERATING ABSTRACTION HIERARCHIES: An Automated Approach to Reducing
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REINFORCEMENT LEARNING, T. S. Sutton
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KNOWLEDGE ACQUISmON: Selected Research and Commentary, S. Marcus
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ISBN: 0-89838-236-X
ATs.T
RULE-BASED PROGRAMMING
by
Thaddeus J. Kowalski
AT&T
Leon S. Levy
AT&T (retired)
KLUWER ACADEMIC PUBLISHERS
Boston / Dordrecht / London
Distributors for North America:
Kluwer Academic Publishers
10 1 Philip Drive
Assinippi Park
Norwell, Massachusetts 02061 USA
Distributors for all other countries:
Kluwer Academic Publishers Group
Distribution Centre
Post Office Box 322
3300 AH Dordrecht, THE NETHERLANDS
Library of Congress Cataloging-in-Publication Data
A C.I.P. Catalogue record for this book is available
from the Library of Congress.
ISBN-13: 978-1-4612-8624-0 e-ISBN-13: 978-1-4613-1435-6
DOl: 10.1007/978-1-4613-1435-6
Copyright <0 1996 by AT&T BELL LABORATORIES
Softcover reprint of the hardcover 1st edition 1996
All rights reserved. No part of this publication may be reproduced, stored in
a retrieval system or transmitted in any form or by any means, mechanical,
photo-copying, recording, or otherwise, without the prior written permission of
the publisher, Kluwer Academic Publishers, 101 Philip Drive, Assinippi Park,
Norwell, Massachusetts 02061
Printed on acid-free paper.
TABLE OF CONTENTS
PROGRAMS ................. '" ............................... '" ...... '" ............. vii
TABLES .................................................................................. .ix
FIGURES .................................................................................. xi
PREFACE ........................................................ '" ...... '" ...... '" ... xiii
ACKNOWLEDGEMENTS ............................................................. xv
INTRODUCTION ........................................................................................... 1
GETTING STARTED IN RULE-BASED PROGRAMMING ...................... 2
CAVEAT ..................................................................................................... 5
C5 ................................................................................................................ 6
S~Y ............................................................................................... 11
OLD FRIENDS REVISITED ........................................................................ 13
THE EUCLIDEAN ALGORITHM ............................................................ 14
FmONACCI SEQUENCE -ITERATIVE ................................................. 15
FIBONACCI SEQUENCE - RECURSIVE ............................................... 16
TOWERS OF HANOI. ............................................................................... 18
TRANSmVE CLOSURE .......................................................................... 23
S~Y ............................................................................................... 28
SEARCH AND BACKTRACKING ............................................................... 29
DEPTH FIRST SEARCH ........................................................................... 32
PROBLEMS AS GRAPHS ......................................................................... 44
GENERATE AND TEST ........................................................................... 58
BACKTRACKING .................................................................................... 76
GENERATORS ......................................................................................... 89
SUMMARy ............................................................................................... 99
AI PARA.DIGMS ........................................................................................ 101
PROOFS ......................................... ;. ....................................................... 102
FORWARD CHAINING PROOFS .......................................................... 104
BACKWARD CHAINING PROOFS ....................................................... 106
HOW AND WHY .................................................................................... III
THE SYSTEM AS A SHELL .................................................................. 115
EMBEDDING - FRAMES ...................................................................... 117
THE OIJKSTRA-LEE PROGRAM .......................................................... 124
SEMANTIC NETS AND CONCEPTUAL GRAPHS ............................... 126
FRAMES ................................................................................................. 131
Rule-Based Programming
CONVERTING SEMANTIC NETS TO FRAMES .................................. 140
OBJECT ORIENTED PROGRAMMING ................................................ 149
SUMMARy ............................................................................................. 154
APPENDIX ............................................................................................. ISS
LANGUAGE PROCESSING ....................................................................... 181
SEMI-mUE SySTEMS .......................................................................... 182
MET APROGRAMMING ......................................................................... 193
CONTEXT -FREE GRAMMARS ............................................................ 1%
TREE EVALUATION - SYNTHESIZED ATTRlBUTES ....................... 203
TREE EVALUATION - INHERITED ATTRlBUTES ............................. 209
TR.EE GRA.MMARS ................................................................................ 213
SUMMARy ............................................................................................. 218
PARTS OF PROLOG AND LISP. .............................................................. 219
DATABASE RETRIEVAL ...................................................................... 220
SIMPLE USER INTERF ACING .............................................................. 223
STATE MACHINE SIMULATION ......................................................... 241
SYMBOLIC SIMPLIFICATION ............................................................. 243
SYMBOLIC DIFFERENTIATION .......................................................... 249
PROGRAMMING IN THE LARGE ........................................................ 2S4
SUMMARy ............................................................................................. 255
.MACHINE LEARNING ............................................................................. 257
CLASSIFICATION ................................................................................. 261
GENERATING ABSTRACTIONS .......................................................... 272
LOCATING A NEW OBJECT IN A HIERARCHY ................................. 276
THE COMPLETE LEARNING DEMONSTRATION MODULE ............. 280
SUMMARy ............................................................................................. 291
REFERENCES ............................................................................................ 293
APPENDIX - QUICK REFERENCE ON C5 - R 2.0 .................................. 295
INDEX ..................................................................................3 01
PROGRAMS
PROGRAM 1.IA THE IF CONSTRUCT OF C!; ...................................................... 7
PROGRAM 1.1BAN EQUIVALENT OPS5 PROGRAM WITHOUT THE IF ............... 7
PROGRAM 1.1A RULE WEIGHTS IN C5 •.....................................•...................... 9
PROGRAM 1.1B SIMULATING THE EFFECT OF RULE WEIGHTS IN OPS5 ........ 10
PROGRAM 1.1 THE EUCLIDEAN ALGoRITHM ..........................•..................... 14
PROGRAM 1.2 ITERATIVE FIBoNACCI SEQUENCE ..................................•..•..•. 16
PROGRAM 1.3 REcURSIVE FIBONACCI SEQUENCE ............•..........................• 17
PROGRAM 2.4 REcuRSIVE TOWERS OF HANOI .............................................. 19
PROGRAM 2.5 ITERATIVE TOWERS OF HANOI ............................................... 21
PROGRAM 1.6 CONTROL SEQUENCING .••.••.••.....•..•.....................•..••............. 24
PROGRAM 1.7 COUNT AND SUM .............................................................•...... 27
PROGRAM 3.1 VERTEX NUMBERING. ..•.....•...........................•...•.....•..•..•........ 30
PROGRAM 3.1 DEPTH-FIRST SEARCH ........................................................... 35
PROGRAM 3.3 DEPTH-FIRST SEARCH WITH EDGE WEIGHTS •..............••....•... 38
PROGRAM 3.4 BREADTH-FIRST SEARCH •••.•.. '" ............................•.•.•............. 41
PROGRAM 3.5 MISSIONARIES AND CANNIBALS - VERSION 1 ...••....... '" .•..•...... 46
PROGRAM 3.6 MISSIONARIES AND CANNIBALS - VERSION 1 ..............•........... 49
PROGRAM 3.7 WOLF, GoAT, AND CABBAGE - VERSION 1 ...•.................•....... 53
PROGRAM 3.8 WOLF, GoAT, AND CABBAGE - VERSION 1 ............................ 55
PROGRAM 3.9 PERMUTATIONS OF 0 •• 4 ...........•...........•....•...•.......................... 59
PROGRAM 3.10 MISSIONARIES AND CANNIBALS - VERSION 3 ........................ 61
PROGRAM 3.11 WOLF, GoAT, AND CABBAGE-VERSION 3 .........•...•............. 68
PROGRAM 3.11 COIN CHANGING - VERSION 1 ...................•.....•..................... 78
PROGRAM 3.13 COIN CHANGING - VERSION 2 .......................•.•..•.................. 82
PROGRAM 3.14 COIN CHANGING - VERSION 3 •..•..•..•.........................••..•..•.... 85
PROGRAM 3.15 8-5-3 BUCKET PROBLEM - VERSION 1 ................•••............... 91
PROGRAM 3.16 8-5-3 BUCKET PROBLEM - VERSION 2 ..........•..............••••••... 95
PROGRAM 4.1 FORWARD CHAINING PROOF ..........•..•..............•..............•.... 104
PROGRAM 4.1 BACKWARD CHAINING PROOF .............••••............................. 106
PROGRAM 4.3 A SIMPLE SoRTING PROGRAM •.••..•..•..•..•..•.................•..•..... 119
PROGRAM 4.4 TOPOLOGICAL SoRTING ............................................•.......... 120
PROGRAM 4.5 CIRCULARITY CHECK. ......•...........................................•..••••. 122
PROGRAM 4.6 THE DlJKSTRA-LEE MINIMUM DISTANCE ••••.•.........•..•..•..•... 124
PROGRAM 4.7 CONVERT A SEMANTIC NET TO A CONCEPTUAL GRAPH ....... 128
PROGRAM 4.8 CONVERT A CONCEPTUAL GRAPH TO A SEMANTIC NET ....... 129
PROGRAM 4.9 FRAMEs -VERSION 1 ....•..•.....•.........................•.•...•.••..•..•..•.• 133
PROGRAM 4.10 FRAMES - VERSION 1 .......................................................... 136
VIll Rule-Based Programming
PROORAM 4.11 FRAMEs - VERSION 3 .......................................................... 138
PROORAM4.12 CONVERTING A SEMANTIC NET TOA FRAME SYSTEM ......... 142
PROORAM 4.13 CONVERTING A FRAME SYSTEM TO A SEMANTIC NET ......... 145
PROORAM 4.14 OBJECT ENCAPSULATION ................................................... 150
PRooRAM 4.15 OBJECT INHERITANCE ....................................................... 152
PROORAM 4.16 AND-OR TREE EXPLANATION SHELL ................................ 155
PRooRAM5.1 SEMI-THUESYSTEM ............................................................. 185
PRooRAM 5.1. TuRING MACHINE ................................................................ 187
PROORAM 5.3 CONTEXT-FREE PARSER ....................................................... 197
PRooRAM5.4 BINARY NUMBER EVALUATION ............................................ 204
PROORAM 5.5 SYNTHESIZED ATTRIBUTES ................................................... 206
PROORAM 5.6 INHERITED AND SYNTHESIZED ATTRIBUTES ......................... 210
PROORAM 5.7 TREE TRANSFORMATION - VERSION 1 .................................. 214
PROORAM 5.8 TREE TRANSFORMATION - VERSION 2 .................................. 216
PROORAM 6.1 DATABASE SEARCH ............................................................... 220
PRooRAM 6.2 INvENTORY SYSTEM - VERSION 1 ......................................... 224
PROORAM 6.3 INvENTORY SYSTEM - VERSION 1 ........................................ 227
PROORAM 6.4 INvENTORY SYSTEM - VERSION 3 ........................................ 233
PROORAM 6.5 FINITE STATE MACHINE WITH USER INTERACTION .............. 242
PROORAM 6.6 SYMBOLIC SIMPLIFICATION .................................................. 244
PRooRAM 6.7 SYMBOLIC DIFFERENTIATION - FRAGMENT ......................... 250
PROORAM 7.1 MERGING ATTRIBUTE VALUES & COMPUTING INHERITANCE 262
PROGRAM 7.1A CLASSIFICATION - OMITTING ATTRIBUTE NAMES IN THE
CODE ................................................................................................... 267
PRooRAM7.2 GENERATING ABSTRACTIONS ................................................ 273
PROORAM 7.3 LINKING TO A HIERARCHY .................................................... 276
PROORAM 7.4 A LEARNING MODULE. ......................................................... 280
TABLES
TABLE 4.1. DESCRIPTION OF NODES OF AND-OR TREE ................................. 112
TABLE 5.1. TRANSITION TABLE OF TuRING MACHINE 'SUBTRACTOR' ............. 188
TABLEA.1 THELHS PATTERN OPERATORS ............................................... 295
TABLE A.2 THE RHS AcrIONs ................................................................... 2%
TABLE A.3 THE RHS FuNcrIONS ............................................................... 297
TABLE A.4 RHS CONTROL STRUcrURES .................................................... 297
TABLEA.5 DEFINITIONS ............................................................................. 298
TABLEA.6 FORMATTINGPRIMITIVES ......................................................... 298
TABLE A. 7 TOP-LEVEL COMMAND DECLARATIONS .................................... 299
TABLE A.S Top LEVEL COMMAND DECLARATIONS .................................... 299
FIGURES
FIGURE 3.1 SEARCH SEQUENCES ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• 33
FIGURE 3.2. PARTIAL GRAPH OF MISSIONARIES AND CANNIBALS •••••••••••••••••• 45
FIGURE 3.3 GRAPHING THE 8-5-3 BUCKET PROBLEM ................................... 90
FIGURE 4.1 AND-OR TREE OF SYSTEM ........................................................... 111
FIGURE 4.2 ALTERNATIVE REPRESENTATIONS OF SEMANTICS .................... 127
FIGURE 4.3. EQUIVALENT SEMANTIC NET AND FRAME REPRESENTATIONS. 141
FIGURE 5.1 STATE DIAGRAM OF A TURING MACHINE ................................. 188
FIGURE 5.2. METAPROGRAMMING .............................................................. 194
FIGURE 5.3. PARSE TREE OF AABABB ........................................................... 199
FIGURE 5.4. PARSETREEOFA*(A+A). .......................................................... 203
FIGURE 5.5. EVALUATION OF BINARY NUMBER 101000 USING SYNTHESIZED
ATTRIBUTES ......................................................................................... 206
FIGURE 5.6. EvA LUA T10N OF ARITHMETIC EXPRESSION (5*7+(-2»/6 USING
SYNTHESIZED ATTRIBUTES ................................................................... 209
FIGURE 5.7. EVALUATION OF BINARY NUMBER 10110101 ............................ 213
FIGURE 5.8. TRANSFORMATION OF AN ARITHMETIC TREE TO A POLISH PREFIX
YIELD TREE .......................................................................................... 216
FIGURE 5.9. OUTPUT OF TRANSFORMATION FROM PREFIX-YIELD TREE TO
INFIX TREE .......................................................................................... 218
FIGURE 7.1 A SIMPLE INHERITANCE STRUCTURE ....................................... 260
FIGURE 7.2 AN INHERITANCE STRUCTURE -AUGMENTED ........................... 261