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. |
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In the 8-puzzle, we are asked to produce a particular problem state, namely, the goal state shown in Figure 1.1. We can also deal with problems for which the goal is to achieve any one of an explicit list of problem states.
A salesman must visit each of the 5 cities shown in the map of Figure 1.5. There is a road between every pair of cities, and the distance is given next to the road. Starting at city A, the problem is to find a route of minimal distance ...
The initial database is the given string of symbols that we want to test. The production rules are derived from the rewrite rules of the grammar ... shown in Figure 1.7. In this simple example, aside from different possible orderings of ...
In Figure 1.8 we have three rules, R1, R2, and R3, that are applicable to the database denoted by SO. ... In producing the database denoted by SG in Figure 1.8, we clearly need consider only one of the many paths shown.
... B, M) and whose termination condition is that the database contain only Ms. Agraph-search control regime might explore many equivalent paths in producing a database containing only Ms. Two of these are shown in Figure 1.9.
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Contents
1 | |
17 | |
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 |