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
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... procedure that makes these tests. In step 3, the procedure orders the rules that are applicable to the database in question. Here, any available heuristic information about the problem domain is used. Those rules that are “guessed ...
... procedure, the entire chain of databases must be an argument of the procedure. Again, practical implementations of AI backtracking production systems use various techniques to avoid the need for explicitly listing all of these databases ...
... procedure fails if it revisits an earlier database. if TERM(DATA), return NIL if DEADEND(DATA), return FAIL if LENGTH(DATALIST) > BOUND, return FAIL; the procedure fails if too many rules have been applied. BOUND is a global variable ...
... procedure would involve the explicit storage of all trial paths so that any of them could be candidates for further extension. For example, in Figure 2.3 we show an initial database, DB1, to which rules R1 and R2, say, are applicable ...
... PROCEDURE* The process of explicitly generating part of an implicitly defined graph can be informally defined as follows. M already on CLOSED, decide for each of its descendants. Procedure GRAPHSEARCH 1 Create a search graph, G ...
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 |