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. |
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... interesting class of problems is concerned with specifying optimal schedules or combinations. ... The problem generalizes to one of finding a minimum cost path over the edges of a graph containing n nodes such that the path visits ...
Supposedly, a node having a low evaluation is more likely to be on an optimal path. The way in which GRAPHSEARCH uses an evaluation function to order nodes can be illustrated by considering again our 8-puzzle example.
Often we are interested in knowing the cost k (s,n) of an optimal path from a given start node, s, to some arbitrary node n. It will simplify our notation somewhat to introduce a new function g” for this purpose.
(This path is the lowest cost path from s to n found so far by the search algorithm. ... Let us say that a search algorithm is admissible if, for any graph, it always terminates in an optimal path from s to a goal node whenever a path ...
Let d”(n) be the length of the shortest path in the implicit graph being searched from s to any node n in the search tree produced by A*. Then since the cost of each arc in the graph is at least some small positive numbere, ...
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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 |