Principles of Artificial Intelligence
A 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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... evaluation function . Evaluation functions have been based on a variety of ideas : Attempts have been made to define the probability that a node is on the best path ; distance or difference metrics between an arbitrary node and the goal ...
... evaluation function . expanded . We see that the same solution path is found here as was found by the other search methods , although the use of the evaluation function has resulted in substantially fewer nodes being expanded . ( If we ...
... evaluation function with a heuristic component . - 3.5 Represent the configuration of a tic - tac - toe board by a ... evaluation function for use by MAX ( playing xs ) to evaluate nonterminal positions . Use this evaluation function to ...
PRODUCTION Systems and AI
SEARCH Strategies FOR
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