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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Suppose the robot perceives a rectangular form. This form, in the context of a room schema, might suggest a window. The window schema might contain the ...
For example, suppose the goal state is 1 2 3 74 86 5 and the initial state is 1 2 5 74 86 3 Any applicable rule applied to the initial state description ...
8 2 l (6) 8 2 1 (7) 8 2 Suppose we decide to use a graph-search control regime in. # | | | : | | & | : # ; | 4 7| 5 (5) # | | # 4 7|5 | # # : 6 (3) 8 2 1 Q) ...
Suppose we decide to use a graph-search control regime in solving the 8-puzzle problem posed in Figure 1.1. We can keep track of the various rules applied ...
Suppose we are given a simple context-free grammar that defines a language. As an example, let the grammar contain the following terminal symbols, ...
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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