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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Página 234
... MYCIN rule looks like : If : ( 1 ) the stain of the organism is gram - positive , and ( 2 ) the morphology of the organism is coccus , and ( 3 ) the growth conformation of the organism is clumps , then there is suggestive evidence ( 0.7 ) ...
... MYCIN rule looks like : If : ( 1 ) the stain of the organism is gram - positive , and ( 2 ) the morphology of the organism is coccus , and ( 3 ) the growth conformation of the organism is clumps , then there is suggestive evidence ( 0.7 ) ...
Página 237
... MYCIN are estimates that are given by experts who write the rules , it is not really necessary to state a more ... MYCIN's techniques and those suggested by Bayesian statistics . We argued at the end of the last section that pure ...
... MYCIN are estimates that are given by experts who write the rules , it is not really necessary to state a more ... MYCIN's techniques and those suggested by Bayesian statistics . We argued at the end of the last section that pure ...
Página 238
... MYCIN combination formula to the three separate rules , we get MB [ h , S1 Ʌ S2 ] = 0.6+ ( 0.60.4 ) = 0.84 MB [ h , ( S1 ^ $ 2 ) ^ $ 3 ] = 0.84 + ( 0.6 · 0.16 ) = 0.936 This is a substantially different result than the true value , as ...
... MYCIN combination formula to the three separate rules , we get MB [ h , S1 Ʌ S2 ] = 0.6+ ( 0.60.4 ) = 0.84 MB [ h , ( S1 ^ $ 2 ) ^ $ 3 ] = 0.84 + ( 0.6 · 0.16 ) = 0.936 This is a substantially different result than the true value , as ...
Contenido
What Is Artificial Intelligence? | 3 |
5 | 24 |
Heuristic Search Techniques | 63 |
Derechos de autor | |
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Términos y frases comunes
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