## 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 249

We elect to

on C2 and its descendant subgoals ) the B - rule ( A C1 ) . ( This manner of

treating an implicational goal was discussed earlier . Now , however , rather than

...

We elect to

**prove**this subgoal by**proving**C2 while having available ( only for useon C2 and its descendant subgoals ) the B - rule ( A C1 ) . ( This manner of

treating an implicational goal was discussed earlier . Now , however , rather than

...

Page 395

21 A net for

Clyde is warm - blooded when we know only that Clyde is an elephant . Again ,

we move up the taxonomic hierarchy to the delineation unit for MAMMALS where

a ...

21 A net for

**proving**that Clyde is gray . Next , suppose we want to**prove**thatClyde is warm - blooded when we know only that Clyde is an elephant . Again ,

we move up the taxonomic hierarchy to the delineation unit for MAMMALS where

a ...

Page 411

28 were marked simply as defaults , for example , we would be at an impasse :

We could

other color . However , we could

, if ...

28 were marked simply as defaults , for example , we would be at an impasse :

We could

**prove**that Clyde was gray only if we could not**prove**that he was anyother color . However , we could

**prove**that he was another color , namely , white, if ...

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### Contents

PROLOGUE | 1 |

PRODUCTION SYSTEMS AND AL | 17 |

SEARCH STRATEGIES FOR | 53 |

Copyright | |

12 other sections not shown

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### Common terms and phrases

achieve actions algorithm AND/OR graph answer applied arcs Artificial Intelligence assume attempt backward block called chapter clauses CLEAR(C complete component condition conjunction consider consistent contains control strategy corresponding cost database deduction Deleters described direction discussed evaluation example expression F-rule fact Figure formula function given global database goal goal wff HANDEMPTY heuristic implication important initial instance involves JOHN knowledge labeled language literals logically match methods move namely node Note obtained occur ONTABLE(A operation path possible precondition predicate calculus problem procedure production system proof prove quantified reasoning refutation represent representation resolution resolvent result robot rule satisfied selected sequence shown in Figure simple solution graph solve specify statement step STRIPS structure subgoal substitutions successors Suppose symbols termination theorem unifying unit University variables