## 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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**achieve**the goal : [ ON ( A , B ) ^ ON ( B , C ) ] . In this particular example , the subgoal space generated by applying all applicable B - rules is larger than the state space that we produced using F - rules . Many of the subgoal ...Page 349

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**achieve**goals have all operated on “ one level . ” When working backward , for example , we investigated ways to**achieve**the goal condition and then to**achieve**all of the subgoals , and so on . In many practical situations , we might ...Page 350

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**achieve**lesser conditions , and so on . This method does not require that the rules themselves be graded according to a hierarchy . We can still have one set of rules . Hierarchical planning is**achieved**by constructing a plan in levels ...### 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 CONT(Y,A contains control regime control strategy cost 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 literal nodes logic monotone restriction natural language processing negation node labeled ONTABLE(A optimal path pickup(A precondition predicate calculus problem-solving procedure production system proof prove recursive regress represent representation resolution refutation result robot problem rule applications search graph search tree selected semantic network sequence shown in Figure Skolem function solution graph solve stack(A STRIPS structure subgoal substitutions successors Suppose symbols termination condition theorem theorem-proving tip nodes universally quantified unstack(C,A variables WORKS-IN