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
... Graph - search Strategies 61 2.3 . Uninformed Graph - search Procedures 68 2.4 . Heuristic Graph - search Procedures 72 2.5 . Related Algorithms 88 2.6 . Measures of Performance 91 2.7 . Bibliographical and Historical Remarks 94 ...
... Graph - search Strategies 61 2.3 . Uninformed Graph - search Procedures 68 2.4 . Heuristic Graph - search Procedures 72 2.5 . Related Algorithms 88 2.6 . Measures of Performance 91 2.7 . Bibliographical and Historical Remarks 94 ...
Page 22
... graph - search control , provision is made for keeping track of the effects of several sequences of rules simultaneously . Various kinds of graph structures and graph searching procedures are used in this type of control . 1.1.4 ...
... graph - search control , provision is made for keeping track of the effects of several sequences of rules simultaneously . Various kinds of graph structures and graph searching procedures are used in this type of control . 1.1.4 ...
Page 25
... search for a solution in the figure ; it is too extensive . Eventually though , a solution path will be found , because all possible paths ( of length less than 6 ) will be explored ... graph - search control 25 PRODUCTION SYSTEMS.
... search for a solution in the figure ; it is too extensive . Eventually though , a solution path will be found , because all possible paths ( of length less than 6 ) will be explored ... graph - search control 25 PRODUCTION SYSTEMS.
Page 27
Nils J. Nilsson. Suppose we decide to use a graph - search control regime in solving the 8 - puzzle problem posed in Figure 1.1 . We can keep track of the various rules applied and the databases produced by a structure called a search ...
Nils J. Nilsson. Suppose we decide to use a graph - search control regime in solving the 8 - puzzle problem posed in Figure 1.1 . We can keep track of the various rules applied and the databases produced by a structure called a search ...
Page 31
... search tree that might be generated by a graph - search control strategy in solving this problem . The numbers next to the edges of the tree are the increments of distance added to the trip by applying the corresponding rule . 1.1.6.2 ...
... search tree that might be generated by a graph - search control strategy in solving this problem . The numbers next to the edges of the tree are the increments of distance added to the trip by applying the corresponding rule . 1.1.6.2 ...
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