Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página 495
... perceptron will output 1 ; if it lies on the other side , the perceptron will output 0. A line that correctly separates the training instances corresponds to a perfectly functioning perceptron . Such a line is called a decision surface ...
... perceptron will output 1 ; if it lies on the other side , the perceptron will output 0. A line that correctly separates the training instances corresponds to a perfectly functioning perceptron . Such a line is called a decision surface ...
Página 498
... perceptron incorrectly fails to fire , but add vector - if x is an input for which the perceptron incorrectly fires . Multiply the sum by a scale factor η . 6. Modify the weights ( wo , W1 , ... , w1 ) by adding the elements of the ...
... perceptron incorrectly fails to fire , but add vector - if x is an input for which the perceptron incorrectly fires . Multiply the sum by a scale factor η . 6. Modify the weights ( wo , W1 , ... , w1 ) by adding the elements of the ...
Página 499
... Perceptron Learning to Solve a Classification Problem two binary inputs , output 1 if exactly one of the inputs is on and output 0 otherwise . We can view XOR as a pattern classification problem in which there are four patterns and two ...
... Perceptron Learning to Solve a Classification Problem two binary inputs , output 1 if exactly one of the inputs is on and output 0 otherwise . We can view XOR as a pattern classification problem in which there are four patterns and two ...
Contenido
5 | 24 |
Heuristic Search Techniques | 63 |
Knowledge Representation Issues | 105 |
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 fact frame 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 operators output parsing particular path perceptron perform players possible preconditions predicate logic problem problem-solving procedure produce PROLOG properties 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