Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página 504
... output layer . During the backward pass , the network's actual output ( from the forward pass ) is compared with the target output and error estimates are computed for the output units . The weights connected to the output units can be ...
... output layer . During the backward pass , the network's actual output ( from the forward pass ) is compared with the target output and error estimates are computed for the output units . The weights connected to the output units can be ...
Página 511
... output units becomes active for any given input . One solution to this problem is to let the network settle , find the output unit with the highest level of activation , and set that unit to 1 and all other output units to 0. In other ...
... output units becomes active for any given input . One solution to this problem is to let the network settle , find the output unit with the highest level of activation , and set that unit to 1 and all other output units to 0. In other ...
Página 513
... output units . Produce : A set of weights such that the output units become active according to some natural division of the inputs . 1. Present an input vector , denoted ( X1 , X2 , ... , Xn ) . 2. Calculate the initial activation for ...
... output units . Produce : A set of weights such that the output units become active according to some natural division of the inputs . 1. Present an input vector , denoted ( X1 , X2 , ... , Xn ) . 2. Calculate the initial activation for ...
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