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
... : : : : : : * : . : : : : Z\ ^ - ZN A /\ ^ D: : Goal The processes 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.
... represent the only ways in which these problems can be solved. The reader may be able to think of good alternatives. 1.1.6.1. A Traveling Salesman Problem. A salesman must visit each of the 5 cities shown in the map of Figure 1.5. There ...
... represented a problem for solution by a production system. Imagine that this production system has a global database ... represent the various ways in which a search tree can be modified by the action of the control strategy of the first ...
... representing unstructured chemical formulas into databases representing partial structures. Any database that contains no unstructured formulas satisfies the termination condition. Briefly, we can illustrate how the structure-proposing ...
... 22 1 + 22 2 = tan w | f : 7. Jas The nodes of the tree represent expressions to be integrated. Fig. 1.13 An AND/OR tree for an integration problem. Fig. 2. 1 Computational costs of AI production systems. 46 PRODUCTION SYSTEMS AND AI.
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 |