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 3
... in this book , we do describe some important methods for knowledge representation and processing that do find ... works in the Purchasing Department , " " Joe Smith was hired on October 8 , 1976 , " " The Purchasing Department has ...
... in this book , we do describe some important methods for knowledge representation and processing that do find ... works in the Purchasing Department , " " Joe Smith was hired on October 8 , 1976 , " " The Purchasing Department has ...
Page 34
... works on a problem in a forward direction and one that works in a backward direction , it is often convenient to make this distinction explicit . When a problem has intuitively clear states and goals and when we choose to employ ...
... works on a problem in a forward direction and one that works in a backward direction , it is often convenient to make this distinction explicit . When a problem has intuitively clear states and goals and when we choose to employ ...
Page 41
... in order to process a component database to termination , the database resulting from just one of the rule ... works for a simple hydrocarbon . The system for generating candidate structures can be viewed as a production system ...
... in order to process a component database to termination , the database resulting from just one of the rule ... works for a simple hydrocarbon . The system for generating candidate structures can be viewed as a production system ...
Page 85
... in determining the heuristic power of search algorithm A. Using h = 0 assures admissibility but results in a breadth ... works quite well for the 8 - puzzle is h ( n ) = P ( n ) + 3S ( n ) . The quantity S ( n ) is a sequence score ...
... in determining the heuristic power of search algorithm A. Using h = 0 assures admissibility but results in a breadth ... works quite well for the 8 - puzzle is h ( n ) = P ( n ) + 3S ( n ) . The quantity S ( n ) is a sequence score ...
Page 128
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Contents
1 | |
17 | |
53 | |
CHAPTER 3 SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS | 99 |
CHAPTER 4 THE PREDICATE CALCULUS IN AI | 131 |
CHAPTER 5 RESOLUTION REFUTATION SYSTEMS | 161 |
CHAPTER 6 RULEBASED DEDUCTION SYSTEMS | 193 |
CHAPTER 7 BASIC PLANGENERATING SYSTEMS | 275 |
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS | 321 |
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS | 361 |
PROSPECTUS | 417 |
BIBLIOGRAPHY | 429 |
AUTHOR INDEX | 467 |
SUBJECT INDEX | 471 |
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Common terms and phrases
8-puzzle achieve actions Adders 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 game tree 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 logic methods monotone restriction negation node labeled ONTABLE(A optimal path pickup(A precondition predicate calculus problem-solving procedure production rules production system proof prove recursive regress represent representation resolution refutation result robot problem rule applications 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