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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A solution to this rewriting problem can be illustrated by a subgraph of the AND/OR graph. Such a solution subgraph is shown by darkened branches in Figure ...
... H A partial AND/OR tree for our C. His problem is shown in Figure 1.11. ... The one indicated by dark lines corresponds to the following structure: ...
Other rules are based on the processes shown in Figure 1.12. A-" |Cs H12] SS Rule Rule H H | | H - C - H |C2Hs! - |-le.
These tendencies are shown informally in Figure 2.1. ... In any given problem, optimum production system efficiency might be obtained from less than ...
In problems for which no arc costs are given, we assume that the arcs have unit cost ... has generated the search graph and search tree shown in Figure 2.4.
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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