Principles of Artificial IntelligenceA classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of the control strategies used. Principles of Artificial Intelligenceevolved from the author's courses and seminars at Stanford University and University of Massachusetts, Amherst, and is suitable for text use in a senior or graduate AI course, or for individual study. |
From inside the book
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... PREDICATE CALCULUS IN AI 131 4.1. Informal. 3.1. 3.2. 3.3. 3.4. 3.5. vii Table of Contents.
... Predicate Calculus 131 4.2. Resolution 145 4.3. The Use of the Predicate Calculus in AI 152 4.4. Bibliographical and Historical Remarks 156 Exercises 156 CHAPTER 5: RESOLUTION REFUTATION SYSTEMS 161 5.1. Production Systems for ...
... Predicate Calculus to Units 362 A Graphical Representation: Semantic Networks 370 Matching 378 Deductive Operations on Structured Objects 387 Defaults and Contradictory Information 408 Bibliographical and Historical Remarks 412 ...
... predicate calculus. The notes on which the book is based evolved in courses and seminars at Stanford University and at the University of Massachusetts at Amherst. Although certain topics treated in my previous book, Problemsolving ...
... predicate calculus, or it might be a loose description, say, in English, that would require further dialogue between the system and the user in order to resolve ambiguities. The task of automatically writing a program to achieve a ...
Contents
1 | |
17 | |
53 | |
CHAPTER 3 SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS | 99 |
CHAPTER 4 THE PREDICATE CALCULUS IN AI | 131 |
CHAPTER 5 RESOLUTION REFUTATION SYSTEMS | 161 |
CHAPTER 6 RULEBASED DEDUCTION SYSTEMS | 193 |
CHAPTER 7 BASIC PLANGENERATING SYSTEMS | 275 |
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS | 321 |
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS | 361 |
PROSPECTUS | 417 |
BIBLIOGRAPHY | 429 |
AUTHOR INDEX | 467 |
SUBJECT INDEX | 471 |