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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... achieve a stated result is closely related to the task of proving that a given program achieves a stated result. The latter is called program verification. Many automatic programming systems produce a verification of the output program ...
... achieve prescribed goals. These methods are illustrated by considering simple problems in robot planning and automatic programming. Chapter 7 introduces some of the more basic ideas, and chapter 8 elaborates on the subjects of complex ...
... achieved excellent results with resolution-based systems [McCharen et al. (1976); Winker and Wos (1978); Winker (1979)]. Boyer and Moore (1979) have developed a theorem-proving system that proves theorems about recursive functions and ...
... achieve any one of an explicit list of problem states. A further generalization is to specify some true/false condition on states to serve as a goal condition. Then the goal would be to achieve any state satisfying this condition. Such ...
... achieve maximum increase in the value of this function by moving the blank up, so our production system selects the corresponding rule. In Figure 1.2 we show the sequence of states traversed by such a production system in solving this ...
Contents
1 | |
17 | |
CHAPTER 2 SEARCH STRATEGIES FOR AI PRODUCTION SYSTEMS | 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 |