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
... node has at most one parent. A node in the tree having no parent is called a root node. A node in the tree having no ... goal set, and each node t in (t; } is a goal node. A graph may be specified either explicitly or implicitly. In an ...
... goal node. 2.2.2. A GENERAL GRAPH-SEARCHING 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 ...
... node in G is also in T. The search tree is defined by the pointers that are set up in step 7. Each node (except s) ... goal node, the process terminates successfully. The successful path from start node to goal node can then be recovered ...
... goal node is generated by putting goal nodes at the very beginning of OPEN; but, of course, this procedure would involve a goal test during step 8 of. Fig. 2.5 A search graph and search tree after expanding node 1. Fig. 2.6A search tree ...
... goal node; they do not save the entire record of the search as do depth-first graph-search strategies.) The search tree generated by a depth-first search process in an 8-puzzle problem is illustrated in Figure 2.6. The nodes are labeled ...
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 |