Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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... sentence In addition , this process will usually assign syntactic categories to all the words in the sentence . This is usually done now because interpretations for affixes ( prefixes and suffixes ) may depend on the syntactic category ...
... sentence In addition , this process will usually assign syntactic categories to all the words in the sentence . This is usually done now because interpretations for affixes ( prefixes and suffixes ) may depend on the syntactic category ...
Página 388
... sentence being parsed . • Bottom - Up Parsing - Begin with the sentence to be parsed and apply the grammar rules backward until a single tree whose terminals are the words of the sentence and whose top node is the start symbol has been ...
... sentence being parsed . • Bottom - Up Parsing - Begin with the sentence to be parsed and apply the grammar rules backward until a single tree whose terminals are the words of the sentence and whose top node is the start symbol has been ...
Página 389
... sentence , such as " Have the students who missed the exam taken it today ? " There are four ways of handling ... sentence . In this example , if the auxiliary verb interpretation of " have " were chosen first and the end of the sentence ...
... sentence , such as " Have the students who missed the exam taken it today ? " There are four ways of handling ... sentence . In this example , if the auxiliary verb interpretation of " have " were chosen first and the end of the sentence ...
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