Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página 232
... given evidence E P ( EH ) the probability that we will observe evidence E given that hypothesis i is true P ( H ) = the a priori probability that hypothesis i is true in the absence of any specific evidence . These probabilities are ...
... given evidence E P ( EH ) the probability that we will observe evidence E given that hypothesis i is true P ( H ) = the a priori probability that hypothesis i is true in the absence of any specific evidence . These probabilities are ...
Página 236
... given two observations is the measure of belief given only one observation plus some increment for the second observation . This increment is computed by first taking the difference between 1 ( certainty ) and the belief given only the ...
... given two observations is the measure of belief given only one observation plus some increment for the second observation . This increment is computed by first taking the difference between 1 ( certainty ) and the belief given only the ...
Página 334
... given state was described by a set of predicates representing the facts that were true in that state . Each distinct state was represented explicitly as part of the predicate . For example , Figure 13.1 shows how a state , called SO ...
... given state was described by a set of predicates representing the facts that were true in that state . Each distinct state was represented explicitly as part of the predicate . For example , Figure 13.1 shows how a state , called SO ...
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