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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... solve . There seems no way to solve this problem by selecting one component , solving it , and then solving the other compo- nent without undoing the solution to the first . We say that the component goals of this problem interact . Solving ...
... solve problems that the other cannot . In fact , by suitable control mechanisms , the problem - solving traces of different types of systems can be made essentially identical . The point is that to solve robot problems efficiently with ...
... solve a variety of problems . Ernst ( 1969 ) presents a formal analysis of the properties of GPS . For an interesting example of applying “ robot ” problem - solving ideas to a domain other than robotics , see Cohen ( 1978 ) , who ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
10 other sections not shown