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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... achieve this regressed goal at the point in the plan just prior to the application of stack ( A , B ) . This ... achieve ON ( B , C ) . These items are eliminated from the stack . The plan to achieve ON ( A , B ) by applying stack ( A ...
... achieve goals have all operated on " one level . " When working backward , for example , we investigated ways to achieve the goal condition and then to achieve all of the subgoals , and so on . In many practical situations , we might ...
... achieve lesser conditions , and so on . This method does not require that the rules themselves be graded according to a hierarchy . We can still have one set of rules . Hierarchical planning is achieved by constructing a plan in levels ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
10 other sections not shown