Artificial Intelligence |
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Página 107
Or we could make use of this representation of a new fact to cause us to take
some appropriate action or to derive representations of additional facts . It is
important to keep in mind that usually the available mapping functions are not
one - to ...
Or we could make use of this representation of a new fact to cause us to take
some appropriate action or to derive representations of additional facts . It is
important to keep in mind that usually the available mapping functions are not
one - to ...
Página 118
Suppose we are interested in the following fact : John spotted Sue . We could
represent this as ' spotted ( agent ( John ) , object ( Sue ) ) Such a representation
would make it easy to answer questions such as : Who spotted Sue ? But now ...
Suppose we are interested in the following fact : John spotted Sue . We could
represent this as ' spotted ( agent ( John ) , object ( Sue ) ) Such a representation
would make it easy to answer questions such as : Who spotted Sue ? But now ...
Página 176
The PROLOG interpreter begins looking for a fact with the predicate apartmentpet
or a rule with that predicate as its head . Usually PROLOG programs are written
with the facts containing a given predicate coming before the rules for that ...
The PROLOG interpreter begins looking for a fact with the predicate apartmentpet
or a rule with that predicate as its head . Usually PROLOG programs are written
with the facts containing a given predicate coming before the rules for that ...
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Contenido
What Is Artificial Intelligence? | 3 |
Problems Problem Spaces and Search | 29 |
Heuristic Search Techniques | 63 |
Derechos de autor | |
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Términos y frases comunes
active addition agents algorithm answer apply approach assertions becomes belief build called Chapter clauses combined complete concept consider consistent constraints contains corresponding define dependency described discussed domain elements example fact Figure function given goal heuristic important initial input instance interpretation John kinds knowledge knowledge base labeled language learning logic look match meaning methods move natural necessary node object occur operators output particular path perform position possible predicate present problem procedure produce properties question reasoning relation represent representation result robot rules semantic sentence shown in Figure shows simple single situation slot solution solve space specific statements step stored structure Suppose task techniques things tree true understanding units usually variables weights