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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... but we describe two types here for purposes of comparison: depth-first search and breadth-first search. The first type of uninformed search orders the ...
In Figure 2.7, we show the search tree generated by a breadth-first search in the 8-puzzle problem. The numbers next to each node indicate the order in ...
2 'g. i : F. : -: :: : :: : : : : : :|: : : : : :: : s: : : S 2.4. HEURISTIC GRAPH-SEARCH PROCEDURES The uninformed search methods, whether breadth-first.
HEURISTIC GRAPH-SEARCH PROCEDURES The uninformed search methods, whether breadth-first or depth-first, are exhaustive methods for finding paths to a goal ...
(If we simply use the evaluation function f(n) = d(n), we get the breadth-first search process.) The choice of evaluation function critically determines ...
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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