An edition of Introduction to artificial intelligence and expert systems (1990)

Introduction to artificial intelligence and expert systems

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Cover of: Introduction to artificial intelligence and expert systems by Dan W. Patterson, Dan W. Patterson
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Last edited by Drini
September 13, 2025 | History
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An edition of Introduction to artificial intelligence and expert systems (1990)

Introduction to artificial intelligence and expert systems

by

  • 12 Want to read

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Publish Date
Publisher
Prentice Hall
Language
English
Pages
448

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Previews available in: English

Subjects

Artificial intelligence, Expert systems (Computer science), Expert systems (computer science), Nonfiction
Edition Availability
Cover of: Introduction to artificial intelligence and expert systems
Introduction to artificial intelligence and expert systems
1990, Prentice Hall
in English
Cover of: Introduction to artificial intelligence and expert systems
Introduction to artificial intelligence and expert systems
1990, Prentice-Hall International
in English

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Book Details

Table of Contents

Preface
Page xiii
Part 1. Introduction to Artificial Intelligence
Page 1
Chapter 1. Overview of Artificial Intelligence
Page 1
1.1. What Is AI?
Page 2
1.2. The Importance of AI
Page 3
1.3. Early Work in AI
Page 5
1.4. AI and Related Fields
Page 7
1.5. Summary
Page 8
Chapter 2. Knowledge: General Concepts
Page 9
2.1. Introduction
Page 9
2.2. Definition and Importance of Knowledge
Page 10
2.3. Knowledge-Based Systems
Page 13
2.4. Representation of Knowledge
Page 14
2.5. Knowledge Organization
Page 16
2.6. Knowledge Manipulation
Page 16
2.7. Acquisition of Knowledge
Page 17
2.8. Summary
Page 17
Exercises
Page 17
Chapter 3. Lisp and Other AI Programming Languages
Page 19
3.1. Introduction to Lisp: Syntax and Numeric Functions
Page 19
3.2. Basic List Manipulation Functions in Lisp
Page 22
3.3. Functions, Predicates, and Conditionals
Page 25
3.4. Input, Output, and Local Variables
Page 29
3.5. Iteration and Recursion
Page 33
3.6. Property Lists and Arrays
Page 35
3.7. Miscellaneous Topics
Page 38
3.8. Prolog and Other AI Programming Languages
Page 40
3.9. Summary
Page 43
Exercises
Page 44
Part 2. Knowledge Representation
Page 47
Chapter 4. Formalized Symbolic Logics
Page 47
4.1. Introduction
Page 47
4.2. Syntax and Semantics for Propositional Logic
Page 49
4.3. Syntax and Semantics for First-Order Predicate Logic
Page 55
4.4. Properties of Well-Formed Formulas
Page 60
4.5. Conversion to Clausal Form
Page 62
4.6. Inference Rules
Page 65
4.7. The Resolution Principle
Page 66
4.8. Nondeductive Inference Methods
Page 73
4.9. Representations Using Rules
Page 75
4.10. Summary
Page 76
Exercises
Page 77
Chapter 5. Dealing with Inconsistencies and Uncertainties
Page 80
5.1. Introduction
Page 81
5.2. Truth Maintenance Systems
Page 82
5.3. Default Reasoning and the Closed World Assumption
Page 87
5.4. Predicate Completion and Circumscription
Page 90
5.5. Modal and Temporal Logics
Page 92
5.6. Fuzzy Logic and Natural Language Computations
Page 97
5.7. Summary
Page 104
Exercises
Page 105
Chapter 6. Probabilistic Reasoning
Page 107
6.1. Introduction
Page 107
6.2. Bayesian Probabilistic Inference
Page 109
6.3. Possible World Representations
Page 113
6.4. Dempster-Shafer Theory
Page 115
6.5. Ad-Hoc Methods
Page 119
6.6. Heuristic Reasoning Methods
Page 122
6.7. Summary
Page 123
Exercises
Page 124
Chapter 7. Structured Knowledge: Graphs, Frames, and Related Structures
Page 126
7.1. Introduction
Page 126
7.2. Associative Networks
Page 127
7.3. Frame Structures
Page 136
7.4. Conceptual Dependencies and Scripts
Page 140
7.5. Summary
Page 144
Exercises
Page 145
Chapter 8. Object-Oriented Representations
Page 147
8.1. Introduction
Page 147
8.2. Overview of Object-Oriented Systems
Page 149
8.3. Objects, Classes, Messages, and Methods
Page 150
8.4. Simulation Example Using an OOS Program
Page 155
8.5. Object-Oriented Languages and Systems
Page 161
8.6. Summary
Page 164
Exercises
Page 165
Part 3. Knowledge Organization and Manipulation
Page 167
Chapter 9. Search and Control Strategies
Page 167
9.1. Introduction
Page 167
9.2. Preliminary Concepts
Page 168
9.3. Examples of Search Problems
Page 170
9.4. Uninformed or Blind Search
Page 174
9.5. Informed Search
Page 178
9.6. Searching And-Or Graphs
Page 184
9.7. Summary
Page 185
Exercises
Page 186
Chapter 10. Matching Techniques
Page 188
10.1. Introduction
Page 188
10.2. Structures Used in Matching
Page 191
10.3. Measures for Matching
Page 194
10.4. Matching Like Patterns
Page 198
10.5. Partial Matching
Page 201
10.6. Fuzzy Matching Algorithms
Page 204
10.7. The RETE Matching Algorithm
Page 205
10.8. Summary
Page 209
Exercises
Page 209
Chapter 11. Knowledge Organization and Management
Page 211
11.1. Introduction
Page 212
11.2. Indexing and Retrieval Techniques
Page 215
11.3. Integrating Knowledge in Memory
Page 219
11.4. Memory Organization Systems
Page 220
11.5. Summary
Page 225
Exercises
Page 225
Part 4. Perception, Communication, and Expert Systems
Page 227
Chapter 12. Natural Language Processing
Page 227
12.1. Introduction
Page 228
12.2. Overview of Linguistics
Page 228
12.3. Grammars and Languages
Page 231
12.4. Basic Parsing Techniques
Page 240
12.5. Semantic Analysis and Representation Structures
Page 255
12.6. Natural Language Generation
Page 259
12.7. Natural Language Systems
Page 264
12.8. Summary
Page 266
Exercises
Page 267
Chapter 13. Pattern Recognition
Page 271
13.1. Introduction
Page 272
13.2. The Recognition and Classification Process
Page 273
13.3. Learning Classification Patterns
Page 277
13.4. Recognizing and Understanding Speech
Page 281
13.5. Summary
Page 282
Exercises
Page 283
Chapter 14. Visual Image Understanding
Page 285
14.1. Introduction
Page 285
14.2. Image Transformation and Low-Level Processing
Page 290
14.3. Intermediate-Level Image Processing
Page 299
14.4. Describing and Labeling Objects
Page 304
14.5. High-Level Processing
Page 312
14.6. Vision System Architectures
Page 317
14.7. Summary
Page 323
Exercises
Page 323
Chapter 15. Expert Systems Architectures
Page 326
15.1. Introduction
Page 327
15.2. Rule-Based System Architectures
Page 330
15.3. Nonproduction System Architectures
Page 337
15.4. Dealing with Uncertainty
Page 347
15.5. Knowledge Acquisition and Validation
Page 347
15.6. Knowledge System Building Tools
Page 349
15.7. Summary
Page 354
Exercises
Page 354
Part 5. Knowledge Acquisition
Page 357
Chapter 16. General Concepts in Knowledge Acquisition
Page 357
16.1. Introduction
Page 357
16.2. Types of Learning
Page 359
16.3. Knowledge Acquisition Is Difficult
Page 360
16.4. General Learning Model
Page 361
16.5. Performance Measures
Page 364
16.6. Summary
Page 365
Exercises
Page 366
Chapter 17. Early Work in Machine Learning
Page 367
17.1. Introduction
Page 367
17.2. Perceptrons
Page 368
17.3. Checker Playing Example
Page 370
17.4. Learning Automata
Page 372
17.5. Genetic Algorithms
Page 375
17.6. Intelligent Editors
Page 378
17.7. Summary
Page 379
Exercises
Page 379
Chapter 18. Learning by Induction
Page 381
18.1. Introduction
Page 381
18.2. Basic Concepts
Page 382
18.3. Some Definitions
Page 383
18.4. Generalization and Specialization
Page 385
18.5. Inductive Bias
Page 388
18.6. Example of an Inductive Learner
Page 390
18.7. Summary
Page 398
Exercises
Page 399
Chapter 19. Examples of Other Inductive Learners
Page 401
19.1. Introduction
Page 401
19.2. The ID3 System
Page 401
19.3. The LEX System
Page 405
19.4. The INDUCE System
Page 409
19.5. Learning Structure Concepts
Page 412
19.6. Summary
Page 413
Exercises
Page 414
Chapter 20. Analogical and Explanation-Based Learning
Page 416
20.1. Introduction
Page 416
20.2. Analogical Reasoning and Learning
Page 417
20.3. Examples of Analogical Learning Systems
Page 421
20.4. Explanation-Based Learning
Page 426
20.5. Summary
Page 430
Exercises
Page 431
References
Page 432
Index
Page 441

Edition Notes

Bibliography: p. 432-440.
Cover title: Introduction to artificial intelligence & expert systems.
Includes index.

Published in
Englewood Cliffs, N.J
Other Titles
Artificial intelligence & expert systems., Introduction to artificial intelligence & expert systems., Artificial intelligence and expert systems.

Classifications

Dewey Decimal Class
006.3
Library of Congress
Q335 .P37 1990

The Physical Object

Pagination
xv, 448 p. :
Number of pages
448

Edition Identifiers

Open Library
OL2212880M
Internet Archive
introductiontoar0000patt
ISBN 10
0134771001
LCCN
89035711
OCLC/WorldCat
20017204
LibraryThing
532936
Goodreads
610715

Work Identifiers

Work ID
OL2942927W

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Download catalog record: RDF / JSON / OPDS | Wikipedia citation
September 13, 2025 Edited by Drini Add TOC from Tocky
December 19, 2023 Edited by ImportBot import existing book
July 16, 2023 Edited by ImportBot import existing book
May 4, 2023 Edited by ImportBot import existing book
April 1, 2008 Created by an anonymous user Imported from Scriblio MARC record