By Neil C. Rowe
Man made Intelligence via Prolog e-book
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Extra info for Artificial Intelligence Through Prolog
Boss(X,Y), not(boss(X,tom)). Notice that the not must come second in the query because X must be bound. html Let us trace execution (see Figure 4-2). 1. The first predicate expression in the query matches only a rule in the database, no facts, so the first job to do is searching for a match for the first expression on the right side of the rule, department(E,D). This can be matched to the first fact, with E=tom and D=sales. 2. Moving on to the second predicate expression in the rule, manager(B,D), the interpreter finds a match in the third fact with B=dick, so the rule succeeds and the first expression in the original query succeeds.
Part_of(X,Y), has(Y,civil_service_system). html which asks for an X that is part of some Y that has a civil service system. Assume the standard database example of this chapter. Then the only facts that will help with this query (the only facts with predicate names part_of and has) are: part_of(enterprise,u_s_navy). part_of(kennedy,u_s_navy). part_of(u_s_navy,u_s_government). has(u_s_government,civil_service_system). Here in detail is what the Prolog interpreter does to answer this query: 1. It takes the first predicate expression in the query, and matches X to enterprise, and Y to u_s_navy.
With joins, possibilities literally multiply. - a_kind_of(enterprise,X), color(X,C). if there are 100 a_kind_of facts and 50 color facts, 50,000 combinations must be tried to find all possible X and C pairs, as when we type a semicolon repeatedly or when there are no such X and C. About long examples We've studied several long examples in this chapter. Are all the examples of artificial intelligence like this? Yes, unfortunately. Artificial intelligence is a set of techniques for managing complexity, and you can only see its advantages in at least moderately complex problems.
Artificial Intelligence Through Prolog by Neil C. Rowe