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
In our discussions of graph-search strategies, we speak as if the various
databases produced by rule applications are actually represented, each in its
entirety, as nodes in a graph or tree. Because these databases are usually very
large ...
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 a subset, T, of G called the search tree.
graph and search tree shown in Figure 2.4. The dark arrows along certain arcs in
this search graph are the pointers that define parents of nodes in the search tree.
The solid nodes are on CLOSED, and the other nodes are on OPEN at the time ...
procedure would involve a goal test during step 8 of GRAPHSEARCH. If the
result is saved, then the goal ... The correspondence would be exact if the graph-
search process generated only one successor at a time. Usually, the
backtracking ...
HEURISTIC GRAPH-SEARCH PROCEDURES The uninformed search methods,
whether breadth-first or depth-first, are exhaustive methods for finding paths to a
goal node. In principle, these methods provide a solution to the path-finding ...
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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 |