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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... slots . Before we can describe such a hierarchy in detail , we need to formalize our notion of a slot . A slot is a relation . It maps from elements of its domain ( the classes for which it makes sense ) to elements of its range ( its ...
... slots . Before we can describe such a hierarchy in detail , we need to formalize our notion of a slot . A slot is a relation . It maps from elements of its domain ( the classes for which it makes sense ) to elements of its range ( its ...
Página 268
... slot . But we often think of them as being properties of a slot associated with a particular class . For example , in Figure 9.5 , we listed two defaults for the batting - average slot , one associated with major league baseball players ...
... slot . But we often think of them as being properties of a slot associated with a particular class . For example , in Figure 9.5 , we listed two defaults for the batting - average slot , one associated with major league baseball players ...
Página 270
... Slot - Values color ( x , y ) Atop - level - part - of ( z , x ) → color ( z , y ) In addition to these domain - independent slot attributes , slots may have domain- specific properties that support problem solving in a particular ...
... Slot - Values color ( x , y ) Atop - level - part - of ( z , x ) → color ( z , y ) In addition to these domain - independent slot attributes , slots may have domain- specific properties that support problem solving in a particular ...
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