## 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 5

The study of theorem proving has been significant in the development of AI

predicate logic, for example, helps us to understand more clearly some of the

components ...

The study of theorem proving has been significant in the development of AI

**methods**. The formalization of the deductive process using the language ofpredicate logic, for example, helps us to understand more clearly some of the

components ...

Page 7

The time taken by the best

problems grows exponentially with problem size. It is not yet known whether

faster

that if a ...

The time taken by the best

**methods**currently known for solving NP-completeproblems grows exponentially with problem size. It is not yet known whether

faster

**methods**(involving only polynomial time, say) exist, but it has been proventhat if a ...

Page 72

HEURISTIC GRAPH-SEARCH PROCEDURES The uninformed search

whether breadth-first or depth-first, are exhaustive

goal node. In principle, these

HEURISTIC GRAPH-SEARCH PROCEDURES The uninformed search

**methods**,whether breadth-first or depth-first, are exhaustive

**methods**for finding paths to agoal node. In principle, these

**methods**provide a solution to the path-finding ...### What people are saying - Write a review

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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