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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These include symbol strings, vectors, sets, arrays, trees, and lists. Sometimes, as in the 8-puzzle, the form of the data structure bears a close ...
Deciding whether a symbol string is a sentence is called the parsing problem, ... As an example, let the grammar contain the following terminal symbols, ...
Suppose we wanted to determine whether or not the following string of symbols is a sentence in the language: The president of the new company approves the ...
Initial The president of the new company approves the sale 1 This sequence of rules replaces terminal symbols by non-terminal symbols.
... node corresponding to a component database satisfying the termination condition (in this case consisting of the symbol M) is enclosed in a double box.
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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