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 vii
... Heuristic Graph - search Procedures 72 2.5 . Related Algorithms 88 2.6 . Measures of Performance 91 2.7 . Bibliographical and Historical Remarks 94 Exercises 96 CHAPTER 3 : Search STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS 99 3.1 ...
... Heuristic Graph - search Procedures 72 2.5 . Related Algorithms 88 2.6 . Measures of Performance 91 2.7 . Bibliographical and Historical Remarks 94 Exercises 96 CHAPTER 3 : Search STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS 99 3.1 ...
Page 9
... heuristic methods for searching the graphs that are implicitly defined by many Al systems . Chapter 3 generalizes these search techniques to extended versions of these graphs , called AND / OR graphs , and to the graphs that arise in ...
... heuristic methods for searching the graphs that are implicitly defined by many Al systems . Chapter 3 generalizes these search techniques to extended versions of these graphs , called AND / OR graphs , and to the graphs that arise in ...
Page 45
... heuristic applicability . In Figure 1.13 we show an AND / OR tree that illustrates a possible search performed by a decomposable production system . The problem is to integrate ( 1 - x2 ) 5/2 dx Algebraic substitutions Example x2dx ( 2 ...
... heuristic applicability . In Figure 1.13 we show an AND / OR tree that illustrates a possible search performed by a decomposable production system . The problem is to integrate ( 1 - x2 ) 5/2 dx Algebraic substitutions Example x2dx ( 2 ...
Page 56
... heuristic merit ) . 4 LOOP : if NULL ( RULES ) , return FAIL ; if there are no ( more ) rules to apply , the procedure fails . 5 R - FIRST ( RULES ) ; the best of the applicable rules is selected . 6 RULES - TAIL ( RULES ) ; the list of ...
... heuristic merit ) . 4 LOOP : if NULL ( RULES ) , return FAIL ; if there are no ( more ) rules to apply , the procedure fails . 5 R - FIRST ( RULES ) ; the best of the applicable rules is selected . 6 RULES - TAIL ( RULES ) ; the list of ...
Page 57
... heuristic information about the problem domain is used . Those rules that are " guessed , " using the heuristic information , most appropriate for that database occur early in the ordering . The applicable rules can be ordered ...
... heuristic information about the problem domain is used . Those rules that are " guessed , " using the heuristic information , most appropriate for that database occur early in the ordering . The applicable rules can be ordered ...
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