Artificial Intelligence, Volumen1McGraw-Hill, 1983 - 436 páginas What is artificial intelligence?; Problem solving; Problems and problem spaces; Basic problem-solving methods; Game playing; Knowledge representation; Knowledge representation using predicate logic; Knowledge representation using other logics; Structured representation of knowledge; Advanced topics; Advanced problem-solving systems; Natural language understanding; Perception; Learning; Implementing A.lI. systems: languages and machines; Conclusion; References; Index. |
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Página 149
... variable . Since variables are just dummy names , this process cannot affect the truth value of the wff . For example , the formula VxP ( x ) \ VxQ ( x ) would be converted to VxP ( x ) \ VyQ ( y ) This step is in preparation for the ...
... variable . Since variables are just dummy names , this process cannot affect the truth value of the wff . For example , the formula VxP ( x ) \ VxQ ( x ) would be converted to VxP ( x ) \ VyQ ( y ) This step is in preparation for the ...
Página 150
... variables are universally quantified , so the prefix can just be dropped and any proof procedure we use can simply assume that any variable it sees is universally quantified . Now the formula produced in step 4 appears as [ ~ Roman ( x ) ...
... variables are universally quantified , so the prefix can just be dropped and any proof procedure we use can simply assume that any variable it sees is universally quantified . Now the formula produced in step 4 appears as [ ~ Roman ( x ) ...
Página 151
... variables in the set of clauses generated in step 8 . By this we mean rename the variables so that no two clauses make refer- ence to the same variable . In making this transformation , we rely on the fact that ( VxP ( x ) Ʌ Q ( x ) ...
... variables in the set of clauses generated in step 8 . By this we mean rename the variables so that no two clauses make refer- ence to the same variable . In making this transformation , we rely on the fact that ( VxP ( x ) Ʌ Q ( x ) ...
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addition algorithm already answer appear applied approach appropriate Artificial Intelligence attempt better block called Chapter choose clauses combined complete concept consider contains corresponding dependency described discussed domain example exploit explore fact frame function given goal grammar graph heuristic important indicates initial input interpretation involved John kinds knowledge labelings language learning logic look machine Marcus match means methods move natural necessary node objects occur operators particular path patterns perform position possible predicate present problem procedure produce prove question reasoning representation represented result rules satisfied script selected semantic sentence shown in Figure shows simple single situation solution solve space specific stack statement step stored structure Suppose task techniques things tion tree true understanding variety