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 35
... difficult . The problems are artificial and highly structured . For other problems , particularly naturally occurring ones , this step is much more difficult . Consider , for example , the task of specifying precisely what it means to ...
... difficult . The problems are artificial and highly structured . For other problems , particularly naturally occurring ones , this step is much more difficult . Consider , for example , the task of specifying precisely what it means to ...
Página 114
... difficult to write a program that can reason about another program's behavior ) and acquisitional efficiency ( because the process of updating and debugging large pieces of code becomes unwieldy ) . As an extreme example , compare the ...
... difficult to write a program that can reason about another program's behavior ) and acquisitional efficiency ( because the process of updating and debugging large pieces of code becomes unwieldy ) . As an extreme example , compare the ...
Página 524
... difficulty doing match- ing . For example , consider the phrases " mouth of a bird " and " nose of a bird . " People ... difficult problems that state- space search addresses ( e.g. , chess , theorem - proving , and planning ) . Parallel ...
... difficulty doing match- ing . For example , consider the phrases " mouth of a bird " and " nose of a bird . " People ... difficult problems that state- space search addresses ( e.g. , chess , theorem - proving , and planning ) . Parallel ...
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