Knowledge-based Systems in Engineering
This book integrates the fundamentals of artifical intelligence (AI) approaches to knowledge representation with engineering examples. Its unified treatment makes it an essential tool in this emerging new field. Combining an informed approach to AI with engineering problem solving, this book is suitable for an introductory course on AI/expert systems which is specifically offered to engineers. The text provides an in-depth appreciation of the AI fundamentals underlying knowledge-based systems and covers rule-based, frame-based, and object-oriented representation with many engineering illustrations.
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DEDUCTION WITH FORMAL LOGIC
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abstraction hierarchy actions activities algorithms approach attributes backward chaining behavior belief revision blackboard architectures breadth-first search building CADD system CDPS Chapter clause Common Lisp complex components constraints database deduction defined depth-first search describe diagnosis discussion domain engineering applications environments evaluation example expert system expertise expression facts frame function goal graphics heuristic high-level ideas implemented inference inference engine inheritance interactive interface KBES applications KBESs kinds knowledge acquisition knowledge base knowledge engineers knowledge representation knowledge sources knowledge-based systems Levitt Lisp LSC Advisor methods Mittal Molgen MYCIN node OARPLAN object-oriented programming objects path perform planners planning systems predicate logic PRIDE problem solving production rules Prolog propositional logic qualitative represent requirements rule-based system SafeQual Section semantic nets SightPlan slot solution specific Stefik strategy structure subclasses subgoals tasks techniques values variables
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Intelligent knowledge-based systems: business and technology in the new ...
Cornelius T. Leondes
No preview available - 2005