## 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 Intelligence evolved 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 80

Thus , A , always expands at least as many nodes as does the more informed Ag . We

Thus , A , always expands at least as many nodes as does the more informed Ag . We

**prove**this result using induction on the depth of a node in the A , search tree at termination . First , we**prove**that if A , expands a node n having ...Page 258

That is , one should not go about attempting to

That is , one should not go about attempting to

**prove**that Sam , say , is an animal by first setting up the subgoal of**proving**that he is a cat and , failing in that , trying the other subgoals . The taxonomic hierarchy branches out too ...Page 395

9.21 A net for

9.21 A net for

**proving**that Clyde is gray . Next , suppose we want to**prove**that Clyde is warm - blooded when we know only that Clyde is an elephant . Again , we move up the taxonomic hierarchy to the delineation unit for MAMMALS where ...### What people are saying - Write a review

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achieve actions algorithm AND/OR graph answer applied arcs assertions assume attempt backtracking backward block called chapter clause CLEAR(C complete component condition consider consistent contains control strategy corresponding cost database Deleters described direction discussed efficient evaluation example expanded expression F-rule fact Figure formula function given global database goal goal node goal stack goal wff HANDEMPTY heuristic important initial involves JOHN knowledge labeled language literals 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 search tree selected sequence shown in Figure simple solution graph solve specify statement step STRIPS structure subgoal substitutions successors Suppose symbols termination unifying unit universal variables