1. Изкуствен интелект Изкуствен интелект Упражнение № 6 спец. Информатика, ФМИ 2004/2005

2. Семантични мрежи и фрейми  Семантични мрежи  Фрейми

3. Семантични мрежи  Семантичните мрежи се състоят от обекти и релации между обектите  Обикновено се представят чрез граф, като възлите на графа съответстват на обектите, а релациите между обектите се представят чрез именувани дъги свързващи възлите на графа

4. Семантичнa мрежa

7. Основни типове връзки

8. Семантична мрежа animal flybirddaylight albatrosskiwibrown walk night Kim black_&_white Albert Ross isa active_atmoving_method isa moving_method active_at colour

9. isa(bird,animal). isa(albatross,bird). isa(kiwi,bird). isa(ross,albatross). isa(albert,albatross). isa(kim,kiwi). moving_method(bird,fly). moving_method(kiwi,walk). active_at(bird,daylight). active_at(kiwi,night). colour(albatross,black_&_white). colour(kiwi,brown). moving_method(X,Method):- isa(X,SuperX), moving_method(SuperX,Method).

10. (де)композиция на терм +Term =.. ?List ?Term =.. +List List е списък, чийто първи елемент е функтор на Term, а останалите елементи на List са аргументите на този терм Term, т.е. | ?- product(0, n, n-1) =.. L. L = [product,0,n,n-1] | ?- n-1 =.. L. L = [-,n,1] | ?- product =.. L. L = [product] | ?- X=..[functor,arg1,arg2,arg3,arg4]. X = functor(arg1,arg2,arg3,arg4) ? Вместо този предикат може да се използват arg/3 и functor/3.

11. fact(Fact):- Fact,!. fact(Fact):- Fact=..[Rel,Arg1,Arg2], isa(Arg1,SuperArg), SuperFact=..[Rel,SuperArg,Arg2], fact(SuperFact).

12. | ?- fact(moving_method(kim,Method)). Method = walk ? | ?- fact(moving_method(albert,Method)). Method = fly ?

13. Съпоставяне на семантични мрежи figure oval polygon 4-sidetriangle ellipsecircle rectangle square trapezoid

14. Съпоставяне на семантични мрежи % is_a hierarchy isa(square,rectangle).isa(rectangle,4-side).isa(trapezoid,4-side).isa(parallelogram,4-side).isa(circle,oval).isa(ellipse,oval).isa(triangle,polygon).isa(4-side,polygon).isa(polygon,figure).isa(oval,figure).

15. c Съпоставяне на семантични мрежи ab c ab c ab c ab Арка support(a,c). touch(a,b).

16. Съпоставяне на семантични мрежи % Objects represented as facts in the format: % object(Name,Parts,IsaRelations, MustRelations,MustNotRelations object(arch,[a,b,c], [isa(a,4-side),isa(b,4-side), isa(c,polygon)], [support(a,c),support(b,c)], [touch(a,b)]).

17. Съпоставяне на семантични мрежи % Test patterns test1([X,Y,Z], [isa(X,rectangle),isa(Y,rectangle),isa(Z,triangle)], [support(X,Z),support(Y,Z)]). test2([X,Y,Z], [isa(X,rectangle),isa(Y,rectangle),isa(Z,triangle)], [support(X,Z),support(Y,Z),touch(X,Y)]).

18. Съпоставяне на семантични мрежи % Sample runs ?- match([X,Y,Z], [isa(X,rectangle),isa(Y,rectangle),isa(Z,triangle)], [support(X,Z),support(Y,Z)], Name). Name=arch ?- test1(Parts,Isa,Rels),match(Parts,Isa,Rels,Name). Name=arch

19. Съпоставяне на семантични мрежи match(Parts,Isa1,Rels,Name) :- object(Name,Parts,Isa2,Must,MustNot), match_isa(Isa1,Isa2), subset(Must,Rels), \+ intersect(Rels,MustNot).

20. Съпоставяне на семантични мрежи match_isa([],[]). match_isa([isa(X,P)|T],[isa(X,Q)|V]) :- parent(P,Q), match_isa(T,V).

21. Съпоставяне на семантични мрежи subset([],_). subset([X|T],Y) :- member(X,Y), subset(T,Y). intersect(L1,L2) :- member(X,L1), member(X,L2).

22. Съпоставяне на семантични мрежи parent(X,X). parent(X,Z) :- isa(X,Y), parent(Y,Z).

23. Opus Opus Name: Opus Friend: Birds 2 Legs: 2 T Flies: T Mammals 4 Legs: 4 Penguins F Flies: F CatsBats Legs: 2 T Flies: T Pat Pat Name: Pat Animals T Alive: T F Flies: F Bill Bill Name: Bill Friend: Subset Member rel(alive,animals,t). rel(flies,animals,f). subset(birds,animals). subset(mammals,animals). rel(flies,birds,t). rel(legs,birds,2). rel(legs,mammals,4). Фрейми

24. Opus Opus Name: Opus Friend: Birds 2 Legs: 2 T Flies: T Mammals 4 Legs: 4 Penguins F Flies: F CatsBats Legs: 2 T Flies: T Pat Pat Name: Pat Animals T Alive: T F Flies: F Bill Bill Name: Bill Friend: Subset Member rel(legs,mammals,4). subset(penguins,birds). subset(cats,mammals). subset(bats,mammals). rel(flies,penguins,f). rel(legs,bats,2). rel(flies,bats,t).

25. Opus Opus Name: Opus Friend: Birds 2 Legs: 2 T Flies: T Mammals 4 Legs: 4 Penguins F Flies: F CatsBats Legs: 2 T Flies: T Pat Pat Name: Pat Animals T Alive: T F Flies: F Bill Bill Name: Bill Friend: Subset Member is_a(opus,penguins). is_a(bill,cats). is_a(pat,bats). name(opus,'Opus'). friend(opus,bill). name(bill,'Bill'). friend(bill,opus). name(Pat,'Pat').

26. Пример FRAME: bird a_kind_of: animal moving_method: fly active_at: daylight

27. Пример FRAME: albatross a_kind_of: bird colour: black_and_white size: 115 % 115 cm long FRAME: kiwi a_kind_of: bird moving_method: walk active_at: night colour: brown size: 40

28. Пример FRAME: Albert instance_of: albatross size: 120

29. % A frame is represented as a set of % Prolog facts: % frame_name(Slot,Value) % where Value is either a simple value or % a procedure % Frame bird: the prototypical bird bird(a_kind_of,animal).bird(movin_method,fly).bird(active_at,daylight). % Frame albatross: albatross is a typical bird % with some extra facts: it is black and white, % and it is 115 cm long albatross(a_kind_of, bird). albatross(colour,black_and_white).albatross(size,115).

30. % Frame kiwi: kiwi is a rather untypical % bird in that it walks instead of flies, % and it is active at night kiwi(a_kind_of,bird).kiwi(moving_method,walk).kiwi(active_at,night).kiwi(colour,brown).kiwi(size,40). % Frame albert: an instance of big albatross albert(instance_of,albatross).albert(size,120). % Frame ross: an instance of baby albatross ross(instance_ot,albatross).ross(size,40).

31. % Frame animal: slot relative_size % obtains its value by executing % procedure relative_size animal(relative_size, execute( execute( relative_size(Object,Value), relative_size(Object,Value), Object, Object, Value Value) ). ).

32. value(Frame,Slot,Value):-Query=..[Frame,Slot,Value],call(Query),!.value(Frame,Slot,Value):-parent(Frame,ParentFrame),value(ParentFrame,Slot,Value).parent(Frame,ParentFrame):-(Query=..[Frame,a_kind_of,ParentFrame] ; Query=..[Frame,instance_of,ParentFrame]), Query=..[Frame,instance_of,ParentFrame]),call(Query).

33. ?-value(albert,active_at,AlbertTime).AlbertTime=daylight?-value(kiwi,active_at,KiwiTime).KiwiTime=night

34. % 40/115*100%=34.78% ?-value(ross,relative_size,R).R=34.78relative_size(Object,RelativeSize):-value(Object,size,ObjSize),value(Object,instance_of,ObjClass), value(ObjClass,size,ClassSize), value(ObjClass,size,ClassSize), RelativeSize is ObjSize/ClassSize*100. animal(relative_size, execute( relative_size(Obj,Val), Obj, Val ) ).

35. value(Frame,Slot,Value):-value(Frame,Frame,Slot,Value).value(Frame,SuperFrame,Slot,Value):-Query=..[SuperFrame,Slot,Information],call(Query),process(Information,Frame,Value).value(Frame,SuperFrame,Slot,Value):-parent(SuperFrame,ParentSuperFrame),value(Frame,ParentSuperFrame,Slot,Value).process(execute(Goal,Frame,Value),Frame,Value):-!,call(Goal).process(Value,_,Value).