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 388
... sentence being parsed . • Bottom - Up Parsing - Begin with the sentence to be parsed and apply the grammar rules backward until a single tree whose terminals are the words of the sentence and whose top node is the start symbol has been ...
... sentence being parsed . • Bottom - Up Parsing - Begin with the sentence to be parsed and apply the grammar rules backward until a single tree whose terminals are the words of the sentence and whose top node is the start symbol has been ...
Página 389
... sentence , such as " Have the students who missed the exam taken it today ? " There are four ways of handling ... sentence . In this example , if the auxiliary verb interpretation of " have " were chosen first and the end of the sentence ...
... sentence , such as " Have the students who missed the exam taken it today ? " There are four ways of handling ... sentence . In this example , if the auxiliary verb interpretation of " have " were chosen first and the end of the sentence ...
Página 425
... sentence , " I gave the apartment manager the key . " • Number agreement , which keeps " trial run " from being interpreted as a sentence in " The first trial run was a failure . " • Case agreement , which rules , out , for example ...
... sentence , " I gave the apartment manager the key . " • Number agreement , which keeps " trial run " from being interpreted as a sentence in " The first trial run was a failure . " • Case agreement , which rules , out , for example ...
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