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 viii
CHAPTER 5 : 5.1 . 5.2 . 5.3 . 5.4 . 5.5 . CHAPTER 6 : CHAPTER 4 : THE PREDICATE CALCULUS IN AI 131 4.1 . Informal Introduction to the Predicate Calculus 131 Resolution 145 The Use of the Predicate Calculus in AI 152 Bibliographical and ...
CHAPTER 5 : 5.1 . 5.2 . 5.3 . 5.4 . 5.5 . CHAPTER 6 : CHAPTER 4 : THE PREDICATE CALCULUS IN AI 131 4.1 . Informal Introduction to the Predicate Calculus 131 Resolution 145 The Use of the Predicate Calculus in AI 152 Bibliographical and ...
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OVERVIEW The book is divided into nine chapters and a prospectus . In chapter 1 , we introduce a generalized production system and emphasize its impor- tance as a basic building block of AI systems .
OVERVIEW The book is divided into nine chapters and a prospectus . In chapter 1 , we introduce a generalized production system and emphasize its impor- tance as a basic building block of AI systems .
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CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS As we discussed in chapter 4 , there are many ways to represent a body of knowledge in the predicate calculus . The appropriateness of a representation depends on the application .
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS As we discussed in chapter 4 , there are many ways to represent a body of knowledge in the predicate calculus . The appropriateness of a representation depends on the application .
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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 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 monotone restriction negation node labeled ONTABLE(A optimal path pickup(A precondition predicate calculus procedure production system 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 stack(A STRIPS structure subgoal substitutions successors Suppose symbols termination condition theorem theorem-proving tip nodes unifying composition universally quantified unstack(C,A WORKS-IN
Bibliographic information
| Title | Principles of Artificial Intelligence |
| Author | Nils J. Nilsson |
| Edition | illustrated, reprint |
| Publisher | Morgan Kaufmann Publishers, 1986 |
| Original from | the University of Virginia |
| Digitized | 27 Jul 2009 |
| ISBN | 0934613109, 9780934613101 |
| Length | 476 pages |
| Export Citation | BiBTeX EndNote RefMan |