Introduction to artificial intelligence and expert systems
By: Dan W. Patterson.
Publisher: Prentice Hall
Published: 1990
Place of publication: Englewood Cliffs, N.J
Language: eng
Number of pages: 448
Subjects: Artificial intelligence.; Expert systems (Computer science)
Other titles: Artificial intelligence & expert systems.; Introduction to artificial intelligence & expert systems.; Artificial intelligence and expert systems.
Notes: Bibliography: p. 432-440.
Cover title: Introduction to artificial intelligence & expert systems.
Includes index.
Table of contents: title: Preface
pagenum: xiii; label: Part 1
title: Introduction to Artificial Intelligence
pagenum: 1; label: Chapter 1
title: Overview of Artificial Intelligence
pagenum: 1; label: 1.1
title: What Is AI?
pagenum: 2; label: 1.2
title: The Importance of AI
pagenum: 3; label: 1.3
title: Early Work in AI
pagenum: 5; label: 1.4
title: AI and Related Fields
pagenum: 7; label: 1.5
title: Summary
pagenum: 8; label: Chapter 2
title: Knowledge: General Concepts
pagenum: 9; label: 2.1
title: Introduction
pagenum: 9; label: 2.2
title: Definition and Importance of Knowledge
pagenum: 10; label: 2.3
title: Knowledge-Based Systems
pagenum: 13; label: 2.4
title: Representation of Knowledge
pagenum: 14; label: 2.5
title: Knowledge Organization
pagenum: 16; label: 2.6
title: Knowledge Manipulation
pagenum: 16; label: 2.7
title: Acquisition of Knowledge
pagenum: 17; label: 2.8
title: Summary
pagenum: 17; title: Exercises
pagenum: 17; label: Chapter 3
title: Lisp and Other AI Programming Languages
pagenum: 19; label: 3.1
title: Introduction to Lisp: Syntax and Numeric Functions
pagenum: 19; label: 3.2
title: Basic List Manipulation Functions in Lisp
pagenum: 22; label: 3.3
title: Functions, Predicates, and Conditionals
pagenum: 25; label: 3.4
title: Input, Output, and Local Variables
pagenum: 29; label: 3.5
title: Iteration and Recursion
pagenum: 33; label: 3.6
title: Property Lists and Arrays
pagenum: 35; label: 3.7
title: Miscellaneous Topics
pagenum: 38; label: 3.8
title: Prolog and Other AI Programming Languages
pagenum: 40; label: 3.9
title: Summary
pagenum: 43; title: Exercises
pagenum: 44; label: Part 2
title: Knowledge Representation
pagenum: 47; label: Chapter 4
title: Formalized Symbolic Logics
pagenum: 47; label: 4.1
title: Introduction
pagenum: 47; label: 4.2
title: Syntax and Semantics for Propositional Logic
pagenum: 49; label: 4.3
title: Syntax and Semantics for First-Order Predicate Logic
pagenum: 55; label: 4.4
title: Properties of Well-Formed Formulas
pagenum: 60; label: 4.5
title: Conversion to Clausal Form
pagenum: 62; label: 4.6
title: Inference Rules
pagenum: 65; label: 4.7
title: The Resolution Principle
pagenum: 66; label: 4.8
title: Nondeductive Inference Methods
pagenum: 73; label: 4.9
title: Representations Using Rules
pagenum: 75; label: 4.10
title: Summary
pagenum: 76; title: Exercises
pagenum: 77; label: Chapter 5
title: Dealing with Inconsistencies and Uncertainties
pagenum: 80; label: 5.1
title: Introduction
pagenum: 81; label: 5.2
title: Truth Maintenance Systems
pagenum: 82; label: 5.3
title: Default Reasoning and the Closed World Assumption
pagenum: 87; label: 5.4
title: Predicate Completion and Circumscription
pagenum: 90; label: 5.5
title: Modal and Temporal Logics
pagenum: 92; label: 5.6
title: Fuzzy Logic and Natural Language Computations
pagenum: 97; label: 5.7
title: Summary
pagenum: 104; title: Exercises
pagenum: 105; label: Chapter 6
title: Probabilistic Reasoning
pagenum: 107; label: 6.1
title: Introduction
pagenum: 107; label: 6.2
title: Bayesian Probabilistic Inference
pagenum: 109; label: 6.3
title: Possible World Representations
pagenum: 113; label: 6.4
title: Dempster-Shafer Theory
pagenum: 115; label: 6.5
title: Ad-Hoc Methods
pagenum: 119; label: 6.6
title: Heuristic Reasoning Methods
pagenum: 122; label: 6.7
title: Summary
pagenum: 123; title: Exercises
pagenum: 124; label: Chapter 7
title: Structured Knowledge: Graphs, Frames, and Related Structures
pagenum: 126; label: 7.1
title: Introduction
pagenum: 126; label: 7.2
title: Associative Networks
pagenum: 127; label: 7.3
title: Frame Structures
pagenum: 136; label: 7.4
title: Conceptual Dependencies and Scripts
pagenum: 140; label: 7.5
title: Summary
pagenum: 144; title: Exercises
pagenum: 145; label: Chapter 8
title: Object-Oriented Representations
pagenum: 147; label: 8.1
title: Introduction
pagenum: 147; label: 8.2
title: Overview of Object-Oriented Systems
pagenum: 149; label: 8.3
title: Objects, Classes, Messages, and Methods
pagenum: 150; label: 8.4
title: Simulation Example Using an OOS Program
pagenum: 155; label: 8.5
title: Object-Oriented Languages and Systems
pagenum: 161; label: 8.6
title: Summary
pagenum: 164; title: Exercises
pagenum: 165; label: Part 3
title: Knowledge Organization and Manipulation
pagenum: 167; label: Chapter 9
title: Search and Control Strategies
pagenum: 167; label: 9.1
title: Introduction
pagenum: 167; label: 9.2
title: Preliminary Concepts
pagenum: 168; label: 9.3
title: Examples of Search Problems
pagenum: 170; label: 9.4
title: Uninformed or Blind Search
pagenum: 174; label: 9.5
title: Informed Search
pagenum: 178; label: 9.6
title: Searching And-Or Graphs
pagenum: 184; label: 9.7
title: Summary
pagenum: 185; title: Exercises
pagenum: 186; label: Chapter 10
title: Matching Techniques
pagenum: 188; label: 10.1
title: Introduction
pagenum: 188; label: 10.2
title: Structures Used in Matching
pagenum: 191; label: 10.3
title: Measures for Matching
pagenum: 194; label: 10.4
title: Matching Like Patterns
pagenum: 198; label: 10.5
title: Partial Matching
pagenum: 201; label: 10.6
title: Fuzzy Matching Algorithms
pagenum: 204; label: 10.7
title: The RETE Matching Algorithm
pagenum: 205; label: 10.8
title: Summary
pagenum: 209; title: Exercises
pagenum: 209; label: Chapter 11
title: Knowledge Organization and Management
pagenum: 211; label: 11.1
title: Introduction
pagenum: 212; label: 11.2
title: Indexing and Retrieval Techniques
pagenum: 215; label: 11.3
title: Integrating Knowledge in Memory
pagenum: 219; label: 11.4
title: Memory Organization Systems
pagenum: 220; label: 11.5
title: Summary
pagenum: 225; title: Exercises
pagenum: 225; label: Part 4
title: Perception, Communication, and Expert Systems
pagenum: 227; label: Chapter 12
title: Natural Language Processing
pagenum: 227; label: 12.1
title: Introduction
pagenum: 228; label: 12.2
title: Overview of Linguistics
pagenum: 228; label: 12.3
title: Grammars and Languages
pagenum: 231; label: 12.4
title: Basic Parsing Techniques
pagenum: 240; label: 12.5
title: Semantic Analysis and Representation Structures
pagenum: 255; label: 12.6
title: Natural Language Generation
pagenum: 259; label: 12.7
title: Natural Language Systems
pagenum: 264; label: 12.8
title: Summary
pagenum: 266; title: Exercises
pagenum: 267; label: Chapter 13
title: Pattern Recognition
pagenum: 271; label: 13.1
title: Introduction
pagenum: 272; label: 13.2
title: The Recognition and Classification Process
pagenum: 273; label: 13.3
title: Learning Classification Patterns
pagenum: 277; label: 13.4
title: Recognizing and Understanding Speech
pagenum: 281; label: 13.5
title: Summary
pagenum: 282; title: Exercises
pagenum: 283; label: Chapter 14
title: Visual Image Understanding
pagenum: 285; label: 14.1
title: Introduction
pagenum: 285; label: 14.2
title: Image Transformation and Low-Level Processing
pagenum: 290; label: 14.3
title: Intermediate-Level Image Processing
pagenum: 299; label: 14.4
title: Describing and Labeling Objects
pagenum: 304; label: 14.5
title: High-Level Processing
pagenum: 312; label: 14.6
title: Vision System Architectures
pagenum: 317; label: 14.7
title: Summary
pagenum: 323; title: Exercises
pagenum: 323; label: Chapter 15
title: Expert Systems Architectures
pagenum: 326; label: 15.1
title: Introduction
pagenum: 327; label: 15.2
title: Rule-Based System Architectures
pagenum: 330; label: 15.3
title: Nonproduction System Architectures
pagenum: 337; label: 15.4
title: Dealing with Uncertainty
pagenum: 347; label: 15.5
title: Knowledge Acquisition and Validation
pagenum: 347; label: 15.6
title: Knowledge System Building Tools
pagenum: 349; label: 15.7
title: Summary
pagenum: 354; title: Exercises
pagenum: 354; label: Part 5
title: Knowledge Acquisition
pagenum: 357; label: Chapter 16
title: General Concepts in Knowledge Acquisition
pagenum: 357; label: 16.1
title: Introduction
pagenum: 357; label: 16.2
title: Types of Learning
pagenum: 359; label: 16.3
title: Knowledge Acquisition Is Difficult
pagenum: 360; label: 16.4
title: General Learning Model
pagenum: 361; label: 16.5
title: Performance Measures
pagenum: 364; label: 16.6
title: Summary
pagenum: 365; title: Exercises
pagenum: 366; label: Chapter 17
title: Early Work in Machine Learning
pagenum: 367; label: 17.1
title: Introduction
pagenum: 367; label: 17.2
title: Perceptrons
pagenum: 368; label: 17.3
title: Checker Playing Example
pagenum: 370; label: 17.4
title: Learning Automata
pagenum: 372; label: 17.5
title: Genetic Algorithms
pagenum: 375; label: 17.6
title: Intelligent Editors
pagenum: 378; label: 17.7
title: Summary
pagenum: 379; title: Exercises
pagenum: 379; label: Chapter 18
title: Learning by Induction
pagenum: 381; label: 18.1
title: Introduction
pagenum: 381; label: 18.2
title: Basic Concepts
pagenum: 382; label: 18.3
title: Some Definitions
pagenum: 383; label: 18.4
title: Generalization and Specialization
pagenum: 385; label: 18.5
title: Inductive Bias
pagenum: 388; label: 18.6
title: Example of an Inductive Learner
pagenum: 390; label: 18.7
title: Summary
pagenum: 398; title: Exercises
pagenum: 399; label: Chapter 19
title: Examples of Other Inductive Learners
pagenum: 401; label: 19.1
title: Introduction
pagenum: 401; label: 19.2
title: The ID3 System
pagenum: 401; label: 19.3
title: The LEX System
pagenum: 405; label: 19.4
title: The INDUCE System
pagenum: 409; label: 19.5
title: Learning Structure Concepts
pagenum: 412; label: 19.6
title: Summary
pagenum: 413; title: Exercises
pagenum: 414; label: Chapter 20
title: Analogical and Explanation-Based Learning
pagenum: 416; label: 20.1
title: Introduction
pagenum: 416; label: 20.2
title: Analogical Reasoning and Learning
pagenum: 417; label: 20.3
title: Examples of Analogical Learning Systems
pagenum: 421; label: 20.4
title: Explanation-Based Learning
pagenum: 426; label: 20.5
title: Summary
pagenum: 430; title: Exercises
pagenum: 431; title: References
pagenum: 432; title: Index
pagenum: 441