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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Page 110
... Figure 3.4 . There is an interesting manner in which the rewrite rules of our example can be used in the reverse direction . We say that such a reverse rule is applicable if the global database contains symbols matching all the symbols ...
... Figure 3.4 . There is an interesting manner in which the rewrite rules of our example can be used in the reverse direction . We say that such a reverse rule is applicable if the global database contains symbols matching all the symbols ...
Page 169
... Figure 5.4 we show how a refutation graph would be generated using this strategy on our example problem . Note that the first level of Figure 5.4 is the same as the first level of Figure 5.2 . At subsequent levels , the linear - input ...
... Figure 5.4 we show how a refutation graph would be generated using this strategy on our example problem . Note that the first level of Figure 5.4 is the same as the first level of Figure 5.2 . At subsequent levels , the linear - input ...
Page 381
... Figure 9.10 , but it is unsuccessful in Figure 9.11 . In any representational scheme there are often several alternative representations for basically the same information . Since our definition of structure matching depends on the ...
... Figure 9.10 , but it is unsuccessful in Figure 9.11 . In any representational scheme there are often several alternative representations for basically the same information . Since our definition of structure matching depends on the ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
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Common terms and phrases
8-puzzle achieve actions Adders AI production algorithm AND/OR graph applied Artificial Intelligence atomic formula backed-up value backtracking backward block breadth-first breadth-first search called chapter clause form CLEAR(C component contains control regime control strategy cost DCOMP Deleters delineation depth-first search described discussed disjunction domain element-of evaluation function example existentially quantified F-rule formula frame problem global database goal expression goal node goal stack goal wff graph-search HANDEMPTY heuristic HOLDING(B implication initial state description knowledge leaf nodes literal nodes logic negation node labeled ONTABLE(A optimal path pickup(A precondition predicate calculus problem-solving procedure production system proof prove recursive regress represent representation result robot problem rule applications search graph search tree selected semantic network sequence shown in Figure Skolem function solution graph solve SRI International stack(A STRIPS structure subgoal substitutions successors Suppose symbols termination condition theorem theorem-proving tip nodes unifying composition universally quantified unstack(C,A variables WORKS-IN