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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For the instance of the 8-puzzle in Figure 12, the. Fig. 1.2 Hill-climbing values for states of the 8-puzzle. Fig. 1.4A search tree for the 8-puzzle.
We can keep track of the various rules applied and the databases produced by a structure called a search tree. An example of such a tree is in Figure 1.4.
... required to represent problems initially and to improve. Fig. 1.4A search tree for the 8-puzzle. Fig. 1.6 A search tree for the traveling salesman problem.
1.6 A search tree for the traveling salesman problem. Fig. 1.8 Equivalent paths in a graph. Fig. 1.9 Solution. 30 PRODUCTION SYSTEMS AND AI.
Figure 1.6 shows part of the search tree that might be generated by a graph-search control strategy in solving this problem. The numbers next to the edges ...
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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