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 67
... basic method in which the first state that is better than the current state is selected . The algorithm works as ... basic hill climbing ) that must be considered when deciding which method will work better for a particular problem ...
... basic method in which the first state that is better than the current state is selected . The algorithm works as ... basic hill climbing ) that must be considered when deciding which method will work better for a particular problem ...
Página 293
... basic types of temporal measures : intervals , and sets of intervals . A number of basic interval properties , such as endsDuring , are defined from the property before , which applies to starting and ending times for events . Sets of ...
... basic types of temporal measures : intervals , and sets of intervals . A number of basic interval properties , such as endsDuring , are defined from the property before , which applies to starting and ending times for events . Sets of ...
Página 533
... basic commonsense notions . These notions help us to decide when to initiate actions , how to reason about others ' actions , and how to determine relationships between events . For instance , if we know that the Franco - Prussian War ...
... basic commonsense notions . These notions help us to decide when to initiate actions , how to reason about others ' actions , and how to determine relationships between events . For instance , if we know that the Franco - Prussian War ...
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