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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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 ...
Imagine that this production system has a global database, rules that can modify it, and a graph-search control strategy that generates a search tree of ...
Various AI programming languages use backtracking as a built-in search strategy [Bobrow and Raphael (1974)]. The literature on heuristic graph searching is ...
1.8 Critically discuss the following thesis: Backtracking (or depth-first graph-search) control strategies should be used when there are multiple paths ...
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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