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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The backtracking process is one way in which the control strategy can be
tentative. A rule is selected, and if it doesn't lead to a solution, the intervening
steps are “forgotten,” and another rule is selected instead. Formally, the
1.8 Critically discuss the following thesis: Backtracking (or depth-first graph-
search) control strategies should be used when there are multiple paths between
problem states because these strategies tend to avoid exploring all of the paths.
We begin our discussion of tentative control by describing backtracking methods.
2.1. BACKTRACKING STRATEGIES In chapter 1 we presented a general
description of the backtracking control strategy and illustrated its use on the 8-
By definition, if a “correct” rule is always first in the ordering, no backtracking will
occur at all. We have used a specific procedure, BACKTRACK, to explain how
backtracking control strategies operate. Several practical concerns—such as the
The 8-puzzle example of backtracking in chapter 1 used BOUND = 7 and also
checked to see if a tile configuration had been visited ... If a level n recursive call
of BACKTRACK fails, control returns to level n – 1 where another rule is tried.
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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