Principles of Artificial IntelligenceA 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. |
From inside the book
It has been found that it is often much more efficient to produce an inexpensive, errorful solution to a ... The problem generalizes to one of finding a minimum cost path over the edges of a graph containing n nodes such that the path ...
Should subsequent computation encounter difficulty in producing a solution, the state of the computation reverts to ... In the second type of tentative control regime, which we call graph-search control, provision is made for keeping ...
A rule is selected, and if it doesn't lead to a solution, the intervening steps are “forgotten,” and another rule is selected ... backtracking allows alternative paths to be pursued. 1.1.43. Graph Search. Graphs (or more specially, ...
Suppose we decide to use a graph-search control regime in solving the 8-puzzle problem posed in Figure 1.1. ... PROBLEMS OF REPRESENTATION Efficient problem solution requires more than an efficient control strategy.
Any trip proposed as a solution must be of minimal distance. 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 of the tree are the ...
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Contents
1 | |
17 | |
CHAPTER 2 SEARCH STRATEGIES FOR AI PRODUCTION SYSTEMS | 53 |
CHAPTER 3 SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS | 99 |
CHAPTER 4 THE PREDICATE CALCULUS IN AI | 131 |
CHAPTER 5 RESOLUTION REFUTATION SYSTEMS | 161 |
CHAPTER 6 RULEBASED DEDUCTION SYSTEMS | 193 |
CHAPTER 7 BASIC PLANGENERATING SYSTEMS | 275 |
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS | 321 |
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS | 361 |
PROSPECTUS | 417 |
BIBLIOGRAPHY | 429 |
AUTHOR INDEX | 467 |
SUBJECT INDEX | 471 |