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 1-3 of 28
Page 34
... direction , it is often convenient to make this distinction explicit . When a problem has intuitively clear states ... direction . The computational effort is the same for both directions . There are occasions , however , when it is more ...
... direction , it is often convenient to make this distinction explicit . When a problem has intuitively clear states ... direction . The computational effort is the same for both directions . There are occasions , however , when it is more ...
Page 110
... direction ) rules are applied to an initial global database consisting of the set { D , E , F , G ) . ( We indicate a reverse direction application of rule R by R ' . ) We note that the production system that results from using these ...
... direction ) rules are applied to an initial global database consisting of the set { D , E , F , G ) . ( We indicate a reverse direction application of rule R by R ' . ) We note that the production system that results from using these ...
Page 258
... direction of rule application . The best direction in which to apply a rule sometimes depends on the domain . As an example of the importance of the direction in which a rule is applied , consider rules that express taxonomic ...
... direction of rule application . The best direction in which to apply a rule sometimes depends on the domain . As an example of the importance of the direction in which a rule is applied , consider rules that express taxonomic ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
10 other sections not shown
Other editions - View all
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(A 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 universally quantified unstack(C,A variables WORKS-IN