Principles of Artificial Intelligence
A 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.
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... Systems 109 Searching Game Trees 112 Bibliographical and Historical Remarks 127 Exercises 128 CHAPTER 4: THE PREDICATE CALCULUS IN AI 131 4.1. Informal.
CHAPTER 4: THE PREDICATE CALCULUS IN AI 131 4.1. Informal Introduction to the Predicate Calculus 131 4.2. Resolution 145 4.3. The Use of the Predicate ...
... and Historical Remarks 357 Exercises 358 STRUCTURED OBJECT REPRESENTATIONS 361 From Predicate Calculus to Units 362 A Graphical Representation: Semantic ...
I stress, in particular, the important roles played in AI by generalized production systems and the predicate calculus. The notes on which the book is based ...
The high-level description might be a precise statement in a formal language, such as the predicate calculus, or it might be a loose description, say, ...
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CHAPTER 3 SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS
CHAPTER 4 THE PREDICATE CALCULUS IN AI
CHAPTER 5 RESOLUTION REFUTATION SYSTEMS
CHAPTER 6 RULEBASED DEDUCTION SYSTEMS
CHAPTER 7 BASIC PLANGENERATING SYSTEMS
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS