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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... logic . Other representational formalisms are discussed in later chapters . The logical formalism is appealing because it immediately suggests a powerful way of de- riving new knowledge from old ... Logic Representing Simple Facts in Logic.
... logic . Other representational formalisms are discussed in later chapters . The logical formalism is appealing because it immediately suggests a powerful way of de- riving new knowledge from old ... Logic Representing Simple Facts in Logic.
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... logic , we can represent real - world facts as statements written as wff's . But a major motivation for choosing to use logic at all is that if we use logical statements as a way of representing knowledge , then we have available a good ...
... logic , we can represent real - world facts as statements written as wff's . But a major motivation for choosing to use logic at all is that if we use logical statements as a way of representing knowledge , then we have available a good ...
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... logics : • Abduction • Inheritance Nonmonotonic Logic One system that provides a basis for default reasoning is Nonmonotonic Logic ( NML ) [ McDermott and Doyle , 1980 ] , in which the language of first - order predicate logic is ...
... logics : • Abduction • Inheritance Nonmonotonic Logic One system that provides a basis for default reasoning is Nonmonotonic Logic ( NML ) [ McDermott and Doyle , 1980 ] , in which the language of first - order predicate logic is ...
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