## 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 66

In this case , each member of M is added to OPEN and is installed in the

execution of the algorithm , and there is no need to change parents of the nodes

in T ...

In this case , each member of M is added to OPEN and is installed in the

**search****tree**as a successor of n . The search graph is the**search tree**throughout theexecution of the algorithm , and there is no need to change parents of the nodes

in T ...

Page 67

graph and

in this search graph are the pointers that define parents of nodes in the

...

graph and

**search tree**shown in Figure 2 . 4 . The dark arrows along certain arcsin this search graph are the pointers that define parents of nodes in the

**search****tree**. The solid nodes are on CLOSED , and the other nodes are on OPEN at the...

Page 80

It is reasonable to say that A * with h ( n ) = W ( n ) is more informed than breadth -

first search , which uses h ( n ) = 0 . We would ... First , we prove that if A ,

expands a node n having zero depth in its

this ...

It is reasonable to say that A * with h ( n ) = W ( n ) is more informed than breadth -

first search , which uses h ( n ) = 0 . We would ... First , we prove that if A ,

expands a node n having zero depth in its

**search tree**, then so will A , . But , inthis ...

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achieve actions algorithm AND/OR graph answer applied arcs Artificial Intelligence assume attempt backtracking backward block called chapter clause CLEAR(C complete component condition consider consistent contains control strategy corresponding cost database deduction Deleters described direction discussed efficient evaluation example expression F-rule fact Figure formula function given goal goal node goal stack goal wff HANDEMPTY heuristic important initial involves JOHN knowledge labeled language literals logic match methods move namely node Note obtained occur ONTABLE(A operation path possible precondition predicate calculus problem procedure production system proof prove quantified reasoning refutation represent representation resolution result robot rule satisfied selected sequence shown in Figure simple solution graph solve specify statement step STRIPS structure subgoal substitutions successors Suppose symbols termination theorem unifying unit University variables