Correo dos exerccios de engenharia do conhecimento em

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Correção dos exercícios de engenharia do conhecimento em Prolog Jacques Robin, DI-UFPE www. di.

Correção dos exercícios de engenharia do conhecimento em Prolog Jacques Robin, DI-UFPE www. di. ufpe. br/~jr

Estudo de caso: a terrível novela Requisitos em Inglês 1. A soap opera is

Estudo de caso: a terrível novela Requisitos em Inglês 1. A soap opera is a TV show whose characters include a husband, a wife and a mailman such that: 2. the wife and the mailman blackmail each other 3. everybody is either alcoholic, drug addict or gay 4. Dick is gay, Jane is alcoholic and Harry is a drug addict 5. the wife is always an alcoholic and the long-lost sister of her husband 6. the husband is always called Dick and the lover of the mailman 7. the long-lost sister of any gay is called either Jane or Cleopatra 8. Harry is the lover of every gay 9. Jane blackmails every drug addicted lover of Dick 10. soap operas are invariably terrible! 0. Who are the characters of a terrible TV show?

Correção do exercício 1: A terrível novela em L 1

Correção do exercício 1: A terrível novela em L 1

Correção do exercício 2: A terrível novela em Prolog tv. Show(Cast, Qual) : soap.

Correção do exercício 2: A terrível novela em Prolog tv. Show(Cast, Qual) : soap. Opera(Cast, Qual). soap. Opera([dick, W, M], terrible) : soap. Cast([dick, W, M]), blackmail(W, M), alcoholic(W), long. Lost. Sister(W, dick), lover(M, dick). soap. Cast([]). soap. Cast([H|T]) : - soap. Char(H), soap. Cast(T). soap. Char(C) : - alcoholic(C). soap. Char(C) : - drug. Addict(C). soap. Char(C) : - gay(C). gay(dick). alcoholic(jane). drug. Addict(harry). lover(harry, G) : - gay(G). long. Lost. Sister(jane, G) : - gay(G). long. Lost. Sister(cleopatra, G) : - gay(G). blackmail(jane, M) : - lover(M, dick), drug. Addict(M). ? -tv. Show(Cast, terrible). * Cast = [dick, jane, harry].

Estudo de caso: o BD acadêmico Requisitos em Inglês 1. Bob is 40 and

Estudo de caso: o BD acadêmico Requisitos em Inglês 1. Bob is 40 and the manager of the CS department. 2. His assistants are John and Sally. 3. Mary’s highest degree is an MS and she works at the CS department. 4. She co-authored with her boss and her friends, John and Sally, a paper published in the Journal of the ACM. 5. Phil is a faculty, who published a paper on FLogic at a Conference of the ACM, jointly with Mary and Bob. 6. Every faculty is a midaged person who writes article, makes in the average $50, 000 a year and owns a degree of some kind, typically a Ph. D. 7. One is considered midage if one is between 30 and 50 years old. 8. A faculty’s boss is both a faculty and a manager. 9. Friends and children of a person are also persons. 10. Every department has a manager who is an employee and assistants who are both employees and students 11. A boss is an employee who is the manager of another employee of the same department. 12. A joint work is a paper that is written by two faculties 13. There are three types of papers: technical reports, journal papers and conference papers 0 a: Who are the midaged employees of the CS department and who are their boss? 0 b: Who published jointly with Mary in the Journal of the ACM? 0 c: Where did Mary published joint work with Phil?

Correção do exercício 3: O banco de dados acadêmico em Prolog 1/ fatos ground

Correção do exercício 3: O banco de dados acadêmico em Prolog 1/ fatos ground person(bob). age(bob, 40). works(bob, cs, faculty). manager(cs, bob). dept(cs). works(john, cs, assistant). study(john, cs). works(sally, cs, assistant). study(sally, cs). hi. Deg(mary, ms). works(mary, cs, faculty). friends(mary, bob). friends(mary, sally). works(phil, cs, faculty). degree(phd). degree(ms). journal(jacm). conf(cacm). article(flogic, [john, sally, mary, bob], jacm). article(florid, [phil, mary, bob], cacm).

Correção do exercício 3: O banco de dados acadêmico em Prolog 2/ regras de

Correção do exercício 3: O banco de dados acadêmico em Prolog 2/ regras de dedução hi. Deg(F, phd) : - works(F, _, faculty), not hi. Deg(F, ms). salary(P, 5000) : - works(F, _, faculty), not salary(F, _). midaged(F) : - age(F, A), !, integer(A), A >= 30, A =< 50. midaged(F) : - works(F, _, faculty). works(B, D, faculty) : - manager(D, B), works(E, D, faculty), !. activity(F, paper. Writing) : works(F, _, faculty). works(S, D, assistant) : - study(S, D), dept(D), works(S, D, _), !. works(M, D, _) : - manager(M, D). boss(B, E) : - manager(D, B), works(E, D, _). person(P 2) : - friends(P 1, P 2), person(P 1). person(C) : - parent(A, C), person(A). person(P) : - study(P, D), dept(D). person(P) : - works(P, _, D), dept(D). report(T, Al, J) : - article(T, Al, J), journal(J). report(T, Al, C) : - article(T, Al, C), conf(C). report(T, Al, D) : - techrep(T, Al, D), dept(D). joint. Work(W, F 1, F 2, P) : - works(F 1, _, faculty), works(F 2, _, faculty), F 1 = F 2, report(W, Fl, P), member(F 1, Fl), member(F 2, Fl). member(H, [H|T]). member(X, [H|T]) : - member(X, T).

Correção do exercício 3: O banco de dados acadêmico em Prolog 3/ consultas midaged.

Correção do exercício 3: O banco de dados acadêmico em Prolog 3/ consultas midaged. Worker. Of(E, D) : - works(E, D, _), midaged(E). boss. Of. Midaged. Worker. Of(B, D) : midaged. Worker. Of(E, D), boss(B, E). ? setof(E, midaged. Worker. Of(E, cs), Le), setof(B, boss. Of. Midaged. Worker. Of(B, cs), Lb). * E = _20, Le = [bob, mary], B = _51, Lb = [bob]; * no. ? setof(F, joint. Work(_, F, mary, jacm), Lf). * F = _20, Lf = [bob]; * no. ? setof(P, joint. Work(_, phil, mary, P), Lp). * P = _20, Lp = [cacm]; * no

Correção do exercício 4: O banco de dados acadêmico em L 1 1/ formulas

Correção do exercício 4: O banco de dados acadêmico em L 1 1/ formulas ground

Correção do exercício 4: O banco de dados acadêmico em L 1 2/ formulas

Correção do exercício 4: O banco de dados acadêmico em L 1 2/ formulas quantificadas

Correção do exercício 4: O banco de dados acadêmico em L 1 3/ consultas

Correção do exercício 4: O banco de dados acadêmico em L 1 3/ consultas

Estudo de caso: A curiosidade matou o gato? * Requisitos em inglês 1. Jack

Estudo de caso: A curiosidade matou o gato? * Requisitos em inglês 1. Jack owns a dog. 2. Every dog owner is an animal lover. 3. No animal lover kills an animal. 4. Either Jack or curiosity killed Tuna 5. Tuna is a cat A. Did curiosity kill the cat? B. Quem matou o gato? * Em L 1 1. $x Dog(x) Ù Owns(Jack, x) 2. "x ($y Dog(y) Ù Owns(x, y)) Þ Animal. Lover(x) 3. "x, y (Animal. Lover(x) Ù Animal(y)) Þ ØKills(x, y) 4. (Kills(Jack, Tuna) Ú Kills(Curiosity, Tuna)) Ù Ø(Kills(Jack, Tuna) Ù Kills(Curiosity, Tuna)) 5. Cat(Tuna) 6. "x Cat(x) Þ Animal(x) 0. Kills(Curiosity, Tuna) B. X, Kills(X, Tuna)

Exercício 5: A curiosidade matou o gatou? em Prolog owns(jack, dog 1). dog(dog 1).

Exercício 5: A curiosidade matou o gatou? em Prolog owns(jack, dog 1). dog(dog 1). animal. Lover(H) : - owns(H, A), animal(A). not. Kills(X, A) : - animal. Lover(X), animal(A), !. not. Kills(X, A) : - not kills(X, A). kills(curiosity, tuna) : - not. Kills(jack, tuna). kills(jack, tuna) : - not. Kills(curiosity, tuna). cat(tuna). animal(A) : - cat(A). animal(A) : - dog(A). ? - kills(curiosity, tuna). yes ? - kills(curiosity, X). X = tuna More (y/n)? y no ? /* 1 */ /* 2 */ /* 3 */ /* 4 */ /* 5 */ /* 6 */ /* 7 */

Exercício 6: A curiosidade matou o gato? em LIFE * Arquivo da curiosidade e

Exercício 6: A curiosidade matou o gato? em LIFE * Arquivo da curiosidade e tuna load("gl. Onto. lf")? animal : = {cat; dog}. dog 1 <| dog. tuna <| cat. feeling <| abst. Obj. curiosity <| feeling. owns(jack, dog 1). love(H, animal) : - owns(H, dog). not. Kills(X, Y) : - love(X, Y), !. not. Kills(X, Y) : - not kills(X, Y). % 6 -7 %1 %5 %1 %2 %3 %3 kills(curiosity, tuna) : - not. Kills(jack, tuna). % 4 kills(jack, tuna) : - not. Kills(curiosity, tuna). % 4 * Arquivo da ontologia geral entities : = {situation; object; quality; quantity; place; time}. situation : = {event; relation}. event : = {action; happening}. object : = {phys. Obj; abst. Obj}. phys. Obj : = {live. Being; artefact}. person <| live. Being. check. List([], Sort) -> true. check. List([Sort|Tail], Sort) -> check. List(Tail). Consultas: > kills(curiosity, tuna)? *** Yes --1> *** No > kills(X, Y)? *** Yes, X = curiosity, Y = tuna. --1> *** No

Estudo de caso: Coloração de mapa * Colorir mapa tal que: * • países

Estudo de caso: Coloração de mapa * Colorir mapa tal que: * • países adjacentes • de cores diferentes A Instância de problema de resolução de restrições A B B C C D D E F

Exercício 7: Coloração de mapa em Prolog

Exercício 7: Coloração de mapa em Prolog

Exercício 8: Coloração de mapa em LIFE

Exercício 8: Coloração de mapa em LIFE