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 57
... heuristic informa- tion , and search procedures using it are called heuristic search methods . It is often possible to specify heuristics that reduce search effort ( below that expended by , say , breadth - first search ) without ...
Nils J. Nilsson. 2.4.6 . THE HEURISTIC POWER OF EVALUATION FUNCTIONS The selection of the heuristic function is crucial in determining the heuristic power of search algorithm A. Using h = 0 assures admissibility but results in a breadth ...
... heuristic compo- nent can be devised for AND / OR graphs . We now describe a search procedure that uses a heuristic function h ( n ) that is an estimate of h * ( n ) , the cost of an optimal solution graph from node n to a set of ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
10 other sections not shown