Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página 182
... rules , then the rules will not be reversible . Some production languages allow only reversible rules ; others do not . When irreversible rules are used , then a commitment to the direction of the search must be made at the time the rules ...
... rules , then the rules will not be reversible . Some production languages allow only reversible rules ; others do not . When irreversible rules are used , then a commitment to the direction of the search must be made at the time the rules ...
Página 184
... rule- based systems , we need to compute the whole set of rules that match the current state description . Backward - chaining systems usually use depth - first backtracking to select individual rules , but forward - chaining systems ...
... rule- based systems , we need to compute the whole set of rules that match the current state description . Backward - chaining systems usually use depth - first backtracking to select individual rules , but forward - chaining systems ...
Página 187
... rule would perform . Preferences Based on Rules There are two common ways of assigning a preference based on the rules themselves . The first , and simplest , is to consider the rules to have been specified in a particular order , such ...
... rule would perform . Preferences Based on Rules There are two common ways of assigning a preference based on the rules themselves . The first , and simplest , is to consider the rules to have been specified in a particular order , such ...
Contenido
Weak SlotandFiller Structures | 9 |
6 | 24 |
Heuristic Search Techniques | 63 |
Derechos de autor | |
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Términos y frases comunes
Abbott algorithm answer apply approach Artificial Intelligence assertions attributes axioms backpropagation backtracking backward backward reasoning belief best-first search breadth-first search Cabot Caesar Chapter clauses concept consider constraints contains contexts contradiction corresponding define depth-first depth-first search described discussed domain example explicitly fact given goal graph heuristic heuristic function Horn clauses important inference inheritance input instance interpretation justification knowledge base knowledge representation labeled learning logical assertions Marcus match move MYCIN node nonmonotonic reasoning object operators particular path perceptron possible preconditions predicate logic problem problem-solving procedure produce production system PROLOG propagation propositional logic question represent resolution result robot rules Section semantic semantic net sentence shown in Figure simple slot solution solve space specific statements step strategy structure Suppose suspect syntactic task techniques theorem things tree true truth maintenance system variables wff's