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 11-15 of 91
... graph that is implicitly defined by s and the successor operator. A graph-search control strategy, then, can be ... or CLOSED). Add these members of M to OPEN. For each member of M that was already on OPEN or CLOSED, decide whether or ...
... or according to heuristic merit. 9 GO LOOP This procedure is sufficiently general to encompass a wide variety of special graph-searching algorithms. The procedure generates an explicit graph, G, called the search graph and ... and the nodes ...
... and thus is generated once only when its unique parent is expanded. Thus, in this special case, the members of M in steps 6 and 7 are not already on either OPEN or ... graph is the search tree throughout the execution of the algorithm, and ...
... graph-search process generated only one successor at a time. Usually, the backtracking implementation is preferred to the depth-first version of GRAPHSEARCH because backtracking is simpler to implement and involves less storage ...
... or depth-first, are exhaustive methods for finding paths to a goal node. In ... and storage available to expend on the search, more efficient alternatives ... Graph-search Procedures.
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 |