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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... electronic circuits; and Genesereth (1978, 1979), for helping casual users of the MACSYMA mathematical formula manipulation system [Martin and Fateman (1971)]. 0.3.4. THEOREM PROVING Early applications of AI ideas to proving 12 PROLOGUE.
... theorem proving. Resolution theorem proving is thoroughly explained in books by Chang and Lee (1973), Loveland (1978), and Robinson (1979). Bledsoe and his co-workers have developed impressive theorem-proving systems for analysis ...
... theorem-proving techniques. Surveys by Biermann (1976) and by Hammer and Ruth (1979) discuss several approaches to automatic programming. The PSI project of Green (1976) includes several components, one of which is a rule-based system ...
... theorems of abstract algebra. [See, for example, Rosen (1973), and Ehrig and Rosen (1977, 1980).] The notion of a decomposable production system encompasses a technique often called problem reduction in AI. [See Nilsson (1971).] The ...
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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 |