## Principios de inteligencia artificialA 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

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Page 68

The resulting search procedure is called uninformed. In AI, we are typically not

interested in uninformed procedures, but we describe two types here for

purposes of comparison: depth-first search and

of ...

The resulting search procedure is called uninformed. In AI, we are typically not

interested in uninformed procedures, but we describe two types here for

purposes of comparison: depth-first search and

**breadth**-**first search**. The first typeof ...

Page 69

The

problem is illustrated in Figure 2.6. ... The

ordering is called

proceeds along ...

The

**search**tree generated by a depth-**first search**process in an 8-puzzleproblem is illustrated in Figure 2.6. ... The

**search**that results from such anordering is called

**breadth**-**first**because expansion of nodes in the**search**treeproceeds along ...

Page 472

Branching factor, of search processes. 92-94

first strategy, in resolution. 165-166 CANCEL relation, in theorem proving. 254-

257. 270 Candidate solution graph. 217-218. 254 Checker-plaving programs, ...

Branching factor, of search processes. 92-94

**Breadth**-**first search**. 69-71 Breadth-first strategy, in resolution. 165-166 CANCEL relation, in theorem proving. 254-

257. 270 Candidate solution graph. 217-218. 254 Checker-plaving programs, ...

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### 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 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 control regime control strategy cost DCOMP delete delineation depth-first search described discussed disjunction domain element-of evaluation function example existentially quantified F-rule formula frame problem game tree global database goal expression goal node goal stack goal wff graph-search HANDEMPTY heuristic implication initial state description knowledge leaf nodes literal nodes logic methods negation node labeled ONTABLE(A optimal path precondition predicate calculus problem-solving procedure production rules production system proof prove recursive regress represent representation resolution refutation result robot problem rule applications rule-based deduction systems search graph search tree semantic network sequence shown in Figure Skolem function solution graph solve STRIPS structure subgoal substitutions successors Suppose symbols termination condition theorem theorem-proving tip nodes unifying composition universally quantified WORKS-IN