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 180
... determining the cause of a patient's illness . To do that , it uses rules that tell it such things as " If the organism has the following set of characteristics as determined by the lab results , then it is likely that it is organism x ...
... determining the cause of a patient's illness . To do that , it uses rules that tell it such things as " If the organism has the following set of characteristics as determined by the lab results , then it is likely that it is organism x ...
Página 313
... determined by the static evaluation function . 2. Otherwise , generate one more ply of the tree by calling the function MOVE- GEN ( Position , Player ) and setting SUCCESSORS to the list it returns . 3. If SUCCESSORS is empty , then ...
... determined by the static evaluation function . 2. Otherwise , generate one more ply of the tree by calling the function MOVE- GEN ( Position , Player ) and setting SUCCESSORS to the list it returns . 3. If SUCCESSORS is empty , then ...
Página 399
... determined . Sometimes only very straightforward information about each word sense is neces- sary . For example , the baseball field interpretation of “ diamond " could be marked as a LOCATION . Then the correct meaning of " diamond ...
... determined . Sometimes only very straightforward information about each word sense is neces- sary . For example , the baseball field interpretation of “ diamond " could be marked as a LOCATION . Then the correct meaning of " diamond ...
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