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. |
From inside the book
Results 1-3 of 18
Page 333
... DCOMP We call our next system for dealing with interacting goals DCOMP . It operates in two main phases . In phase 1 , DCOMP produces a tentative " solution , " assuming that there are no goal interactions . Goal expressions are ...
... DCOMP We call our next system for dealing with interacting goals DCOMP . It operates in two main phases . In phase 1 , DCOMP produces a tentative " solution , " assuming that there are no goal interactions . Goal expressions are ...
Page 334
... DCOMP examines the tentative solution graph for goal interactions . Certain rules , for example , destroy the preconditions needed by rules in other branches of the graph . These interactions force additional constraints on the order of ...
... DCOMP examines the tentative solution graph for goal interactions . Certain rules , for example , destroy the preconditions needed by rules in other branches of the graph . These interactions force additional constraints on the order of ...
Page 339
... DCOMP first - phase solution with the adders and deleters listed for each condition . Note that , compared with Figure 8.2 , there are fewer deleters of the HANDEMPTY predicates because we have two hands . During the second phase of ...
... DCOMP first - phase solution with the adders and deleters listed for each condition . Note that , compared with Figure 8.2 , there are fewer deleters of the HANDEMPTY predicates because we have two hands . During the second phase of ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
10 other sections not shown
Other editions - View all
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 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