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
... results of rule applications. These successor nodes are called OR nodes because in order to process a component database to termination, the database resulting from just one of the rule applications must be processed to termination. In ...
... results in high rule application costs because it generally needs to try a large number of rules to find a solution. To inform a control system completely about the problem domains of interest in AI typically involves a high-cost ...
... result in minimal rule application costs; they guide the production system directly to a solution. These tendencies are shown informally in Figure 2.1. The overall computational cost of an AI production system is the combined rule ...
... result in failures. Only the path currently being extended is stored explicitly. A more flexible procedure would involve the explicit storage of all trial paths so that any of them could be candidates for further extension. For example ...
... result that the search tree may contain several nodes labeled by the same database. Node repetitions, of course, lead to redundant successor computations. Hence, there is a tradeoff between the computational cost of testing for matching ...
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 |