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 189
... Knowledge about which paths are most likely to lead quickly to a goal state is often called search control knowledge . It can take many forms : 1. Knowledge about which states are more preferable to others . 2. Knowledge about which ...
... Knowledge about which paths are most likely to lead quickly to a goal state is often called search control knowledge . It can take many forms : 1. Knowledge about which states are more preferable to others . 2. Knowledge about which ...
Página 289
... knowledge and see where the difficulties crop up . In other words , one strategy is to focus temporarily on the content of knowledge bases rather than on their form . • Shared Knowledge - Small knowledge - based systems must make ...
... knowledge and see where the difficulties crop up . In other words , one strategy is to focus temporarily on the content of knowledge bases rather than on their form . • Shared Knowledge - Small knowledge - based systems must make ...
Página 553
... knowledge engineer interviews a domain expert to elucidate expert knowledge , which is then translated into rules . After the initial system is built , it must be iteratively refined until ... KNOWLEDGE ACQUISITION 553 Knowledge Acquisition.
... knowledge engineer interviews a domain expert to elucidate expert knowledge , which is then translated into rules . After the initial system is built , it must be iteratively refined until ... KNOWLEDGE ACQUISITION 553 Knowledge Acquisition.
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