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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... representing actions . 4.3.4 Representing Sets of Objects It is important to be able to represent sets of objects for several reasons . One is that there are some properties that are true of sets that are not true of the individual ...
... representing actions . 4.3.4 Representing Sets of Objects It is important to be able to represent sets of objects for several reasons . One is that there are some properties that are true of sets that are not true of the individual ...
Página 132
... represent real - world facts as logical propositions written as well - formed formulas ( wff's ) in propositional ... represent the obvious fact stated by the classical sentence Socrates is a man . We could write : SOCRATESMAN But if we ...
... represent real - world facts as logical propositions written as well - formed formulas ( wff's ) in propositional ... represent the obvious fact stated by the classical sentence Socrates is a man . We could write : SOCRATESMAN But if we ...
Página 254
... represent objects that exist independently of their relationship to each other . But now suppose we want to represent the fact that John is taller than Bill , using the net John HI height Bill height greater - than H2 The nodes H1 and ...
... represent objects that exist independently of their relationship to each other . But now suppose we want to represent the fact that John is taller than Bill , using the net John HI height Bill height greater - than H2 The nodes H1 and ...
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