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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... goal node. In principle, these methods provide a solution to the path-finding problem, but they are often infeasible ... definition, it is not necessary (though it is a common misconception) that a search method with more heuristic power ...
... definition implies g(n) > g”(n). For the estimate h(n), of h”(n), we rely on heuristic information from the problem ... goal. We now show that if h is a lower bound on h” (that is, if h (n) < h"(n) for all nodes n), then algorithm A ...
... goal node exists, A* will terminate even for infinite graphs. To do so, let us suppose the opposite, that A* does ... definition off for A*, we have f(n) = g(n) + h (n'). We know that A* has already found an optimal path to n' since n ...
... goal node. Now A* selected n before termination, so at this time (by RESULT 2) we know that there existed on OPEN ... definition seems intuitively reasonable, since with h bounded from above by h" for admissibility, one suspects that ...
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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