Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas A revision of an established text for undergraduate and postgraduate Artificial Intelligence courses, this text incorporates the latest research and methods. |
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Página 57
... stable compound will be formed , so later addition of z will have no effect ; if z is added to y , however , a different stable compound may be formed , so later addition of x will have no effect . Nonpartially commutative production ...
... stable compound will be formed , so later addition of z will have no effect ; if z is added to y , however , a different stable compound may be formed , so later addition of x will have no effect . Nonpartially commutative production ...
Página 489
... stable state , i.e. , until no more units can change state . This process is called parallel relaxation . If the network starts in the state shown in Figure 18.1 , the unit in the lower left corner will tend to activate the unit above ...
... stable state , i.e. , until no more units can change state . This process is called parallel relaxation . If the network starts in the state shown in Figure 18.1 , the unit in the lower left corner will tend to activate the unit above ...
Página 490
... stable state . There can be no divergence or oscillation . The network can be used as a content - addressable memory by setting the activities of the units to correspond to a partial pattern . To retrieve a pattern , we need only supply ...
... stable state . There can be no divergence or oscillation . The network can be used as a content - addressable memory by setting the activities of the units to correspond to a partial pattern . To retrieve a pattern , we need only supply ...
Contenido
What Is Artificial Intelligence? | 3 |
5 | 24 |
Heuristic Search Techniques | 63 |
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 example fact 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 ON(C operators output parsing particular path perceptron perform players possible preconditions predicate logic problem problem-solving procedure produce PROLOG 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