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 547
Elaine Rich, Kevin Knight. Chapter 20 Expert Systems Expert systems solve problems ( such as the ones in Figure 1.1 ) that are normally solved by human " experts . " To solve expert - level problems , expert systems need access to a ...
Elaine Rich, Kevin Knight. Chapter 20 Expert Systems Expert systems solve problems ( such as the ones in Figure 1.1 ) that are normally solved by human " experts . " To solve expert - level problems , expert systems need access to a ...
Página 549
... expert systems exploit many of the representation and reasoning mechanisms that we have discussed . Because these programs are usually written primarily as rule - based ... systems , and 20.2 . EXPERT SYSTEM SHELLS 549 Expert System Shells.
... expert systems exploit many of the representation and reasoning mechanisms that we have discussed . Because these programs are usually written primarily as rule - based ... systems , and 20.2 . EXPERT SYSTEM SHELLS 549 Expert System Shells.
Página 556
... expert systems , much progress has been made in the construction of such programs . Experience gained in these efforts suggests the following conclusions : ⚫ These systems derive their power from a great deal of domain - specific ...
... expert systems , much progress has been made in the construction of such programs . Experience gained in these efforts suggests the following conclusions : ⚫ These systems derive their power from a great deal of domain - specific ...
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