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 197
... FACT EXPRESSIONS An AND / OR graph can be used to represent a fact expression in AND / OR form . For example , the AND / OR tree of Figure 6.1 repre- sents the fact expression that we just put into AND / OR form above . Each ...
... FACT EXPRESSIONS An AND / OR graph can be used to represent a fact expression in AND / OR form . For example , the AND / OR tree of Figure 6.1 repre- sents the fact expression that we just put into AND / OR form above . Each ...
Page 215
... fact expressions used by our backward system are limited to those in the form of a conjunction of literals . Such expressions can be represented as a set of literals . Analogous to the forward system , when a fact literal matches a ...
... fact expressions used by our backward system are limited to those in the form of a conjunction of literals . Such expressions can be represented as a set of literals . Analogous to the forward system , when a fact literal matches a ...
Page 257
... fact graph . ) The termination condition we have just described is adequate for many problems but would fail to detect that the goal graph follows from the fact graph in Figure 6.31 . A more general sort of " fact - goal " resolution ...
... fact graph . ) The termination condition we have just described is adequate for many problems but would fail to detect that the goal graph follows from the fact graph in Figure 6.31 . A more general sort of " fact - goal " resolution ...
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 CONT(Y,A 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 logic negation node labeled ONTABLE(A optimal path pickup(A precondition predicate calculus problem-solving procedure production system proof prove recursive regress represent representation result robot problem rule applications search graph search tree selected semantic network sequence shown in Figure Skolem function solution graph solve SRI International stack(A STRIPS structure subgoal substitutions successors Suppose symbols termination condition theorem theorem-proving tip nodes universally quantified unstack(C,A variables WORKS-IN