Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas A revision of an established text for undergraduate and postgraduate Artificial Intelligence courses, this text incorporates the latest research and methods. |
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Elaine Rich, Kevin Knight. Chapter 20 Expert Systems Expert systems solve problems ( such as the ones in Figure 1.1 ) that are normally solved by human " experts . " To solve expert - level problems , expert systems need access to a ...
Elaine Rich, Kevin Knight. Chapter 20 Expert Systems Expert systems solve problems ( such as the ones in Figure 1.1 ) that are normally solved by human " experts . " To solve expert - level problems , expert systems need access to a ...
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... expert to elucidate expert knowledge , which is then translated into rules . After the initial system is built , it must be iteratively refined until it approximates expert - level performance . This process is expensive and time ...
... expert to elucidate expert knowledge , which is then translated into rules . After the initial system is built , it must be iteratively refined until it approximates expert - level performance . This process is expensive and time ...
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... expert systems than ones with common sense . • An expert system is usually built with the aid of one or more experts , who must be willing to spend a great deal of effort transferring their expertise to the system . • Transfer of ...
... expert systems than ones with common sense . • An expert system is usually built with the aid of one or more experts , who must be willing to spend a great deal of effort transferring their expertise to the system . • Transfer of ...
Contenido
What Is Artificial Intelligence? | 3 |
5 | 24 |
Heuristic Search Techniques | 63 |
Derechos de autor | |
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Abbott agents algorithm answer apply approach ARMEMPTY assertions attributes axioms backpropagation backtracking backward belief best-first search breadth-first search Caesar called Chapter chess clauses complete concept conceptual dependency consider constraints contains contradiction corresponding define depth-first depth-first search described discussed domain example fact function game tree goal grammar graph heuristic Horn clauses important inference inheritance input instance interpretation isa links John justification knowledge base knowledge representation labeled learning Marcus match minimax move MYCIN natural language node object ON(B ON(C operators output parsing particular path perceptron perform players possible preconditions predicate logic problem problem-solving procedure produce PROLOG represent result robot rules script Section semantic semantic net sentence shown in Figure simple slot solution solve specific step structure Suppose syntactic task techniques theorem things tree truth maintenance system understanding variables version space