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 178
... reason forward from the initial state and to reason backward from the goal state . To reason forward , the left sides ( the preconditions ) are matched against the current state and the right sides ( the results ) are used to generate ...
... reason forward from the initial state and to reason backward from the goal state . To reason forward , the left sides ( the preconditions ) are matched against the current state and the right sides ( the results ) are used to generate ...
Página 216
... reasons for such belief , with valid justifications being our " good " reasons . Notice that the label OUT may indicate that we have specific reason to believe that a node represents an assertion that is not true , or it may mean simply ...
... reasons for such belief , with valid justifications being our " good " reasons . Notice that the label OUT may indicate that we have specific reason to believe that a node represents an assertion that is not true , or it may mean simply ...
Página 423
... reason for wanting R done , A must have a reason for assuming that B can do R , A must have a reason for assuming that B is willing to do R , and A must have a reason for assuming that B was not already planning to do R. Reasonableness ...
... reason for wanting R done , A must have a reason for assuming that B can do R , A must have a reason for assuming that B is willing to do R , and A must have a reason for assuming that B was not already planning to do R. Reasonableness ...
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