I am using the below family database to practice prolog. I want to...
'Find the first name and surname of mothers whose children’s combined incomes are
greater than £140,000, where at least one child is unemployed. The rule should also return
the first name of the unemployed child/children, and the value of the children’s combined
incomes'
so far I have this code...Help would be appreciated, really struggling on this exercise. thanks :)
(Fname,Sname,Income):-
family(person(_,_,_,_),person(Fname,Sname,_,_),Children),
total(Children,Income),
Income > 140000.
.
total([Person|List],Sum):-
salary(Person,S), % S: salary of the first person
total(List,Rest), % Rest: sum of salaries of others
Sum is S + Rest.
.
family(
person(pat,marx,date(10,march,1944),unemployed),
person(charlotte,marx,date(11,february,1946),unemployed),
[
person(aine,marx,date(17,april,1985),unemployed),
person(louis,marx,date(25,june,1980),works(harriott,32000)),
person(pearl,marx,date(10,june,1981),unemployed),
person(pat_jr,marx,date(11,march,1983),works(world_of_food,850000)),
person(ricky,marx,date(18,february,1987),unemployed)
]
).
family(
person(fred,chomsky,date(3,october,1955),works(bean_counters,100000)),
person(sarah,chomsky,date(19,october,1961),works(supercomms, 60000)),
[
person(amos,chomsky,date(1,july,1984),works(sell_cell, 80000))
]
).
family(
person(ted,marx,date(10,july,1948),unemployed),
person(adelheid,marx,date(9,december,1948),unemployed),
[ person(ted_jr,marx,date(14,april,1988),works(world_of_food,90000)),
person(jenny,marx,date(23,may,1984),unemployed),
person(margaret,marx,date(23,may,1984),unemployed),
person(sadie,marx,date(23,may,1984),unemployed),
person(louis,marx,date(22,august,1979),unemployed),
person(alan,marx,date(9,may,1990),unemployed)
]
).
family(
person(ted,russell,date(21,may,1938),retired),
person(victoria,russell,date(9,november,1944),retired),
[ person(betty,russell,date(18,august,1971),works(boat_house,65000)),
person(jack,russell,date(27,may,1965),works(green_machine,15000)),
person(joan,russell,date(9,april,1963),works(green_machine,15000)),
person(penelope,russell,date(9,april,1963),works(green_machine,15000)),
person(enda,russell,date(2,november,1968),works(exc-u-vate,15000)),
person(amos,russell,date(27,may,1965),works(green_machine,15000)),
person(algernon,russell,date(2,november,1968),works(exc-u-vate,15000)),
person(cal,russell,date(9,october,1970),works(sell_cell,30000))
]
).
family(
person(bill,kant,date(7,august,1942),works(fibrefast,100000)),
person(ann,kant,date(9,october,1945),works(roulada,100000)),
[ person(mark,kant,date(25,april,1970),works(harriott,36000)),
person(cal,kant,date(22,december,1966),works(harriott,35000)),
person(simon,kant,date(27,january,1965),works(harriott,31000)),
person(sol,kant,date(17,november,1964),unemployed),
person(andrew,kant,date(9,march,1968),works(harriott,32000)),
person(joan,kant,date(27,january,1965),works(harriott,34000))
]
).
family(
person(ted,russell,date(6,june,1950),works(mopper-ups,25000)),
person(helen,russell,date(10,june,1951),works(harriott,110000)),
[ person(maura,russell,date(21,february,1972),works(sparrow_hotel,19000)),
person(simon,russell,date(24,december,1970),works(zoom-away,50000)),
person(victoria,russell,date(23,january,1971),works(volts,49000)),
person(andrew,russell,date(24,june,1969),works(sparrow_hotel,35000)),
person(cal,russell,date(15,april,1974),works(sparrow_hotel,55000)),
person(milly,russell,date(21,february,1972),works(sparrow_hotel,19000))
]
).
This is a very odd database layout, but that doesn't need to stop us. First the head of the rule with the things we're going to return:
q(MotherFirst, MotherLast, UnemployedKids, CombinedIncome) :-
We're considering families here, so let's match them and pull out the mother's info:
family(_, person(MotherFirst, MotherLast, _, _), Children),
The underscores there correspond to the father, the mother's date-of-birth and occupation. None of those are relevant to the problem so forget 'em. Next we need to do some processing on the kids: we need to find the ones that are unemployed and get the combined income. I will do two traversals because it's simpler for me. First the sum of their income:
total_income(Children, CombinedIncome),
CombinedIncome > 140000,
unemployed(Children, UnemployedKids),
UnemployedKids = [_|_]. % ensure we have at least one unemployed kid
I've broken the task down a little bit; let's go ahead and write some helpers:
% compute the total income for a list of people
total_income([], 0).
total_income([person(_, _, _, works(_, Amount) | People], Total) :-
total_income(People, Subtotal),
Total is Subtotal + Amount.
% find the unemployed people in a list of people
unemployed([], []).
unemployed([person(FN, LN, DOB, unemployed) | People],
[FN | Unemployed]) :-
!, % cut so that we don't enter the next rule with someone who is unemployed
unemployed(People, Unemployed).
unemployed([_|People], Unemployed) :- unemployed(People, Unemployed).
Both of those could be simplified considerably using library(aggregate) or even some folds (perhaps with library(lambda) but this is a straightforward "classic" (wordy) solution.
Related
I can't seem to wrap my head around how Prolog actually works. I'm very used to other programming languages like Java and Python but Prolog seems to be very different since it is based on a set of logical statements.
If someone can explain to me how I would approach a situation where I am given a set of rules such as
likes(john,mary).
likes(mary,adam).
likes(adam,mary).
likes(jack,destiny).
likes(destiny,adam).
likes(brianna,adam).
and I want to find out how to see who is the most liked person (in this case adam = 3), how would I do this?
Maybe it's easier if you think of Prolog as a special database retrieval language that can morph into functional programming in the same line.
Here we we have a relation likes/2 over which we want to run statistics.
One could use predicates from library(aggregate) or similar, but let's not
Suggestion is to chain three operations:
Create a nicer structure to run stats
Run stats over nicer structure
Find the best
Create nicer structure to run stats
Collect
the vector (in the form or a Prolog list) of persons that occur as second argument in predicate likes/2 (so that we have something to count), and
the set of persons (also in the form of a Prolog list) so that we can iterate over something.
The key are the collection predicates findall/3 and setof/3
findall/3 is used to collect all the Person that appear on second argument position of likes/2,
setof/3 is used to collect the set of all Person that appear on first or second argument position of likes/2.
To make that work, setof/3 needs to be told that the argument on the other position is unimportant by
"existentially quantifying" it with X^.
person_occurrences(PersonVec) :-
findall(Person,likes(_,Person),PersonVec).
person_set(PersonSet) :-
setof(Person,X^(likes(Person,X);likes(X,Person)),PersonSet).
Alternativey for person_set/2, more comprehensible:
person(Person) :- likes(Person,_).
person(Person) :- likes(X,Person).
person_set(PersonSet) :- setof(Person,person(Person),PersonSet).
Trying this on the "Prolog Toplevel" shows we are on the right track:
?- person_occurrences(PersonSet).
PersonSet = [mary, adam, mary, destiny, adam, adam].
?- person_set(PersonSet).
PersonSet = [adam, brianna, destiny, jack, john, mary].
We can easily count how often a person occurs in the vector of persons,
by using findall/3 to create an arbitrary list of x (for example),
one x for each occurrence, then determining the length of that list:
count(Person,PersonVec,Count) :-
findall(x,member(Person,PersonVec),Xs),length(Xs,Count).
Trying this on the "Prolog Toplevel" shows we are on the right track:
?- person_occurrences(PersonVec),count(mary,PersonVec,Count).
PersonVec = [mary, adam, mary, destiny, adam, adam],
Count = 2.
We now have the "nicer structure" that we can use to do stats, namely the
"vector of persons" and the "set of persons".
Run stats over nicer structure
The result here, called Stats shall be a list (it's always lists) of
pairs -(NumberOfOccurrencesOfPersonInPersonVector,Person),
which can be more easily written "infix": Count-Person, for example 2-mary.
This is a recursive definition (or an inductive definition) whereby we "count"
for each person element in PersonSet until the PersonSet is the empty set
(or rather, the empty list), upon which we are done and succeed. The result
is constructed in the third argument:
% stats(PersonVec,PersonSet,Stats)
stats(_,[],[]).
stats(PersonVec,[Person|MorePersons],[Count-Person|MoreStats]) :-
count(Person,PersonVec,Count), % count them
stats(PersonVec,MorePersons,MoreStats). % recursion
Trying this on the "Prolog Toplevel" shows we are on the right track:
?- person_occurrences(PersonVec),stats(PersonVec,[mary],Stats).
PersonVec = [mary, adam, mary, destiny, adam, adam],
Stats = [2-mary] ; % Maybe more solutions?
false. % Nope.
New we can build the whole of the stats list:
stats(Stats) :-
person_occurrences(PersonVec),
person_set(PersonSet),
stats(PersonVec,PersonSet,Stats).
Trying this on the "Prolog Toplevel" shows we are on the right track:
?- stats(Stats).
Stats = [3-adam, 0-brianna, 1-destiny, 0-jack, 0-john, 2-mary] ;
false.
Find the best
Given Stats, we can find a BestPerson by maximizing over the list of pairs.
This can be done directly by selecting the pair which is "largest"
according to "the standard order of term": the numeric count comes first
so a term with a larger numeric count is "larger" than one with a
smaller numeric count, which is what we want. The predicate
max_member/2
does what we want:
best(Stats,BestPerson,BestCount) :-
max_member(BestCount-BestPerson,Statss).
Alternatively, we can program-out the max_member/2 (and keep
it to numeric comparison of the first argument, AND get several
answers in case there are several persons with the same "likes"
count), like so:
% start the maximization over Stats with a dummy "(-1)-nobody"
best(Stats,BestPerson,BestCount) :-
best2(Stats, (-1)-nobody, BestCount-BestPerson).
% best2(Stats,BestCountSoFar-BestPersonSoFar,Result).
best2([],BestCountSoFar-BestPersonSoFar,BestCountSoFar-BestPersonSoFar).
best2([Count-_|MoreStats],BestCountSoFar-BestPersonSoFar,Result) :-
Count < BestCountSoFar,
best2(MoreStats,BestCountSoFar-BestPersonSoFar,Result). % keep best
best2([Count-_|MoreStats],BestCountSoFar-BestPersonSoFar,Result) :-
Count == BestCountSoFar,
best2(MoreStats,BestCountSoFar-BestPersonSoFar,Result). % keep best (2nd possibility below)
best2([Count-Person|MoreStats],BestCountSoFar-_,Result) :-
Count >= BestCountSoFar,
best2(MoreStats,Count-Person,Result). % take new, better, pair
Conclude
We run it together:
?- stats(Stats),best(Stats,BestPerson,BestCount).
Stats = [3-adam, 0-brianna, 1-destiny, 0-jack, 0-john, 2-mary],
BestPerson = adam, BestCount = 3 ; % maybe more solutions?
false. % no
Complete code
likes(john,mary).
likes(mary,adam).
likes(adam,mary).
likes(jack,destiny).
likes(destiny,adam).
likes(brianna,adam).
person_occurrences(PersonVec) :-
findall(Person,likes(_,Person),PersonVec).
person_set(PersonSet) :-
setof(Person,X^(likes(Person,X);likes(X,Person)),PersonSet).
count(Person,PersonVec,Count) :-
findall(x,member(Person,PersonVec),Xs),length(Xs,Count).
% stats(PersonVec,PersonSet,Stats)
stats(_,[],[]).
stats(PersonVec,[Person|MorePersons],[Count-Person|MoreStats]) :-
count(Person,PersonVec,Count), % count them
stats(PersonVec,MorePersons,MoreStats). % recursion
stats(Stats) :-
person_occurrences(PersonVec),
person_set(PersonSet),
stats(PersonVec,PersonSet,Stats).
% start the maximization over Stats with a dummy "(-1)-nobody"
best(Stats,BestPerson,BestCount) :-
best2(Stats, (-1)-nobody, BestCount-BestPerson).
% best2(Stats,BestCountSoFar-BestPersonSoFar,Result).
best2([],BestCountSoFar-BestPersonSoFar,BestCountSoFar-BestPersonSoFar).
best2([Count-_|MoreStats],BestCountSoFar-BestPersonSoFar,Result) :-
Count < BestCountSoFar,
best2(MoreStats,BestCountSoFar-BestPersonSoFar,Result). % keep best
best2([Count-_|MoreStats],BestCountSoFar-BestPersonSoFar,Result) :-
Count == BestCountSoFar,
best2(MoreStats,BestCountSoFar-BestPersonSoFar,Result). % keep best (2nd possibility below)
best2([Count-Person|MoreStats],BestCountSoFar-_,Result) :-
Count >= BestCountSoFar,
best2(MoreStats,Count-Person,Result). % take new, better, pair
Consider the set of facts:
likes(john,mary).
likes(mary,adam).
likes(adam,mary).
likes(jack,destiny).
likes(destiny,adam).
likes(brianna,adam).
Another possible solution is as follows:
You can use setof/3 to get the list of persons that like someone:
?- setof(Person, likes(Person,Someone), ListOfPersons).
Someone = adam,
ListOfPersons = [brianna, destiny, mary] ;
Someone = destiny,
ListOfPersons = [jack] ;
Someone = mary,
ListOfPersons = [adam, john].
Then, you can combine setof/3 with findall/3 to get a list of pairs of the form Someone-ListOfPersons:
?- findall(Someone-ListOfPersons, setof(Person, likes(Person,Someone), ListOfPersons), Pairs).
Pairs = [adam-[brianna, destiny, mary], destiny-[jack], mary-[adam, john]].
After that, you can use maplist/3 to map pairs of the form Someone-ListOfPersons into corresponding pairs of the form Someone-NumberOfPersons:
?- findall(Someone-ListOfPersons, setof(Person, likes(Person,Someone), ListOfPersons), Pairs),
maplist([Someone-ListOfPersons, Someone-NumberOfPersons]>>length(ListOfPersons,NumberOfPersons), Pairs, NewPairs).
Pairs = [adam-[brianna, destiny, mary], destiny-[jack], mary-[adam, john]],
NewPairs = [adam-3, destiny-1, mary-2].
Finally, you can use sort/4 to get the most liked person:
?- findall(Someone-ListOfPersons, setof(Person, likes(Person,Someone), ListOfPersons), Pairs),
maplist([Someone-ListOfPersons, Someone-NumberOfPersons]>>length(ListOfPersons,NumberOfPersons), Pairs, NewPairs),
sort(2,>=,NewPairs, SortedPairs).
Pairs = [adam-[brianna, destiny, mary], destiny-[jack], mary-[adam, john]],
NewPairs = [adam-3, destiny-1, mary-2],
SortedPairs = [adam-3, mary-2, destiny-1].
Thus, the final solution is:
most_liked(Person) :-
findall(Someone-ListOfPersons,
setof(Person, likes(Person,Someone), ListOfPersons),
Pairs),
maplist([Someone-ListOfPersons, Someone-NumberOfPersons]>>length(ListOfPersons, NumberOfPersons),
Pairs,
NewPairs),
sort(2, >=, NewPairs, [Person-_|_]).
Running example:
?- most_liked(Person).
Person = adam.
Another solution where we don't care about the admonition to "do things only once" and "let Prolog work for us" instead is simply this:
Determine how much an arbitrary person is "liked"
person_liked_count(Person,Count) :-
likes(_,Person), % Grab a Person
findall(x, % Create a list of 'x'
likes(_,Person), % one 'x' for each like of the Person
Xs), % and this will be list 'Xs'.
length(Xs,Count). % The number of likes is the length of the list
We now get multiple solutions for any person, but we don't care:
?- person_liked_count(Person,Count).
Person = mary, Count = 2 ;
Person = adam, Count = 3 ;
Person = mary, Count = 2 ;
Person = destiny, Count = 1 ;
Person = adam, Count = 3 ;
Person = adam, Count = 3.
Maximize by doing exactly what is demanded
Person with "likes count" Count is what we want if we have person_liked_count(Person,Count) and there is no other person that has higher count (there is no need to even check that _PersonOther is different from Person inside the negation-as-failure-marked-subgoal, although we can):
most_liked(Person,Count) :-
person_liked_count(Person,Count), % grab a Person and a Count
\+ (person_liked_count(_P,CountOther), % "where not exists" a person _P
CountOther > Count). % with a higher count
We now get several answers, but that is not a problem as they are all the same:
?- most_liked(Person,Count).
Person = adam, Count = 3 ;
Person = adam, Count = 3 ;
Person = adam, Count = 3.
We can always force determinism with once/1
?- once(most_liked(Person,Count)).
Person = adam, Count = 3.
Everything in one block
likes(john,mary).
likes(mary,adam).
likes(adam,mary).
likes(jack,destiny).
likes(destiny,adam).
likes(brianna,adam).
person_liked_count(Person,Count) :-
likes(_,Person), % Grab a Person
findall(x, % Create a list of 'x'
likes(_,Person), % one 'x' for each like of the Person
Xs), % and this will be list 'Xs'.
length(Xs,Count). % The number of likes is the length of the list
most_liked(Person,Count) :-
person_liked_count(Person,Count), % grab a Person and a Count
\+ (person_liked_count(_P,CountOther), % "where not exists" a person _P
CountOther > Count). % with a higher count
solution(Person,Count) :- once(most_liked(Person,Count)).
I'm trying to write a predicate that calculates which destination a group of friends will visit.
The friends list their countries of preferences like this
choice(marie, [peru,greece,vietnam]).
choice(jean, [greece,peru,vietnam]).
choice(sasha, [vietnam,peru,greece]).
choice(helena,[peru,vietnam,greece]).
choice(emma, [greece,peru,vietnam]).
I want to write a predicate called where that takes 2 arguments to perform the calculation.
The formula I have in mind is that the first country is worth 3 points, the second one is worth 2 points, and the last one is worth 1 point.
Here's an example of what I'm trying to achieve.
?- where([marie,jean,sasha,helena,emma],Country).
peru .
So far I have this
where([], X).
where([H|T], N) :- choice(H, [A|B]), where(T,N).
It lets me iterate through all the different friends and shows their choices but I can't iterate through the list of choices and assign points to the destinations.
How should I go about iterating through the list of choices for each friend and assigning points to calculate the best destination?
While this will solve your problem, I know it uses many predicates that you have not seen. So think of this an opportunity to excel and learn a lot.
Even if you don't understand it all, there is enough detail and intermediate results in the test that you should be able to navigate your way to a proper solution you create.
Also this is by no means efficient, it was just a quick proof of concept I did to see how this could be done.
choice(marie, [peru,greece,vietnam]).
choice(jean, [greece,peru,vietnam]).
choice(sasha, [vietnam,peru,greece]).
choice(helena,[peru,vietnam,greece]).
choice(emma, [greece,peru,vietnam]).
destinations(Destinations) :-
findall(D1,choice(_,D1),D2),
flatten(D2,D3),
list_to_set(D3,Destinations).
init_weights(Destinations,Weights) :-
empty_assoc(Assoc),
init_weights(Destinations,Assoc,Weights).
init_weights([],Weights,Weights).
init_weights([H|T],Assoc0,Weights) :-
put_assoc(H,Assoc0,0,Assoc1),
init_weights(T,Assoc1,Weights).
update_weights([C1,C2,C3],Weights0,Weights) :-
del_assoc(C1,Weights0,Value0,Weights1),
Value1 is Value0 + 3,
put_assoc(C1,Weights1,Value1,Weights2),
del_assoc(C2,Weights2,Value2,Weights3),
Value3 is Value2 + 2,
put_assoc(C2,Weights3,Value3,Weights4),
del_assoc(C3,Weights4,Value4,Weights5),
Value5 is Value4 + 1,
put_assoc(C3,Weights5,Value5,Weights).
person_weight(Person,Weights0,Weights) :-
choice(Person,[C1,C2,C3]),
update_weights([C1,C2,C3],Weights0,Weights).
people(People) :-
findall(Person,choice(Person,_),People).
choice(Destination) :-
destinations(Destinations),
init_weights(Destinations,Weights0),
people(People),
update_choices(People,Weights0,Weights1),
cross_ref_assoc(Weights1,Weights),
max_assoc(Weights, _, Destination),
true.
cross_ref_assoc(Assoc0,Assoc) :-
assoc_to_list(Assoc0,List0),
maplist(key_reverse,List0,List),
list_to_assoc(List,Assoc).
key_reverse(Key-Value,Value-Key).
update_choices([],Weights,Weights).
update_choices([Person|People],Weights0,Weights) :-
person_weight(Person,Weights0,Weights1),
update_choices(People,Weights1,Weights).
Tests
:- begin_tests(destination).
test(destinations) :-
destinations([peru, greece, vietnam]).
test(init_weights) :-
destinations(Destinations),
init_weights(Destinations,Weights),
assoc_to_list(Weights,[greece-0, peru-0, vietnam-0]).
test(update_weights) :-
destinations(Destinations),
init_weights(Destinations,Weights0),
update_weights([peru,greece,vietnam],Weights0,Weights),
assoc_to_list(Weights,[greece-2,peru-3,vietnam-1]).
test(person_weight) :-
destinations(Destinations),
init_weights(Destinations,Weights0),
person_weight(jean,Weights0,Weights),
assoc_to_list(Weights,[greece-3,peru-2,vietnam-1]).
test(people) :-
people([marie,jean,sasha,helena,emma]).
test(update_choices) :-
destinations(Destinations),
init_weights(Destinations,Weights0),
people(People),
update_choices(People,Weights0,Weights),
assoc_to_list(Weights,[greece-10,peru-12,vietnam-8]).
test(cross_ref_assoc) :-
List0 = [1-a,2-b,3-c],
list_to_assoc(List0,Assoc0),
cross_ref_assoc(Assoc0,Assoc),
assoc_to_list(Assoc,[a-1,b-2,c-3]).
test(choice) :-
choice(peru).
:- end_tests(destination).
As suggested by GuyCoder, you need an accumulator to sum each person preferences, and foldl/N allows to does exactly this.
choice(marie, [peru,greece,vietnam]).
choice(jean, [greece,peru,vietnam]).
choice(sasha, [vietnam,peru,greece]).
choice(helena,[peru,vietnam,greece]).
choice(emma, [greece,peru,vietnam]).
where(People,Where) :-
foldl([Person,State,Updated]>>(choice(Person,C),update(State,C,Updated)),
People,
[0=greece,0=peru,0=vietnam],
Pref),
aggregate(max(S,S=W),member(S=W,Pref),max(_,_=Where)).
% sort(Pref,Sorted),
% last(Sorted,_=Where).
update(S0,[A,B,C],S3) :-
update(S0,3,A,S1),
update(S1,2,B,S2),
update(S2,1,C,S3).
update(L,V,C,U) :-
append(X,[Y=C|Z],L),
P is Y+V,
append(X,[P=C|Z],U).
I have left commented the last two goals replaced by the single goal aggregate/3, so you can try to understand the syntax...
Data:
%flight(FID, Start, Destination, Company, Seats).
%------------------------------------------------------
flight(1, 'Paris', 'Berlin', 'Lufthansa', 210).
flight(2, 'Frankfurt', 'Dubai', 'Lufthansa', 400).
flight(3, 'Rome', 'Barcelona', 'Eurowings', 350).
I want to know all companies that, that have flights with over 200 seats. But each company should be returned only once.
I tried:
q1(Company) :- flight(_, _, _, Company, S), S > 200.
But this returns lufthansa twice. I tried:
q1(Company) :- flight(_, _, _, Company, S), S > 200,!.
But this exited after first return of Lufthansa. I think I have to wrap the condition in a sub query:
q1(Company) :- flight(_, _, _, Company, S), q12(S).
q12(S) :- flight(_, _, _, _, S), S > 200,!.
But this exited after the first return, too. Any idea how I can return a company that matches only once using cut?
FID is the primary key and I am only allowed to use . , + < > <= >=
As I said in the comments, one way to do this is to use setof/3 to obtain a sorted list of results without duplicates, for example:
?- setof(C, q1(C), Cs).
This is a recommended way to remove redundant solutions. You can enumerate such solutions for example with:
?- setof(C, q1(C), Cs), member(C, Cs).
Viewer discretion is advised for the remainder...
There are also several ways to solve this subject to brain-damaged conditions that an unskilled instructor may impose on you. For example, here is an inefficient and highly non-idiomatic way to obtain all companies that occur in your database without using setof/3:
companies(Cs) :-
companies_([], Cs).
companies_(Cs0, Cs) :-
( flight(_, _, _, C, _),
\+ memberchk(C, Cs0) ->
companies_([C|Cs0], Cs)
; Cs0 = Cs
).
I don't have the stomach to carry this further, so I just end with the hint for you: You only need to insert one goal to solve your task. I hope your teacher is happy with this "solution".
The key here are the unique IDs. Your original question is:
Which companies have flights with over 200 seats?
The query is obvious:
?- flight(_,_,_,C,S), S > 200.
C = 'Lufthansa',
S = 210 ;
C = 'Lufthansa',
S = 400 ;
C = 'Eurowings',
S = 350.
Now, because the IDs are unique, there is going to be a flight within the group with the same company and seats > 200 which has the highest (or lowest) ID. So, you could re-formulate your question as:
Which flights have over 200 seats and the highest ID within the group of flights from the same company?
or, to make if a bit more close to the way that we can pose the query in Prolog,
Given a flight with an ID, Company, and Seats, the Seats must be more than 200, and there must be no other flight from the same company with a higher ID.
?- flight(ID,_,_,C,S), S > 200, \+ ( flight(IDX,_,_,C,_), IDX > ID ).
ID = 2,
C = 'Lufthansa',
S = 400 ;
ID = 3,
C = 'Eurowings',
S = 350.
If you put this query in a predicate you can avoid reporting the ID and the actual number of seats.
By the way, this approach is a courtesy of this answer to a somewhat related question (shameless self-promotion). I really can't remember where I got the idea: I am certain I didn't come up with it myself. If anyone can find a good reference here on Stackoverflow or elsewhere please comment.
I am working through sample questions while studying, using SWI-Prolog. I have reached the last section of this question, where I have to recursively (I hope) compare elements of a list containing 'researcher' structures to determine whether or not the researchers have the same surname, and, if they do, return the Forename and Surname of the group leader for that list.
There is only one list that meets this criteria and it has four members, all with the same surname. However, the correct answer is returned FOUR times. I feel my solution is inelegant and is lacking. Here is the question:
The following Prolog database represents subject teaching teams.
% A research group structure takes the form
% group(Crew, Leader, Assistant_leader).
%
% Crew is a list of researcher structures,
% but excludes the researcher structures for Leader
% and Assistant_leader.
%
% researcher structures take the form
% researcher(Surname, First_name, expertise(Level, Area)).
group([researcher(giles,will,expertise(3,engineering)),
researcher(ford,bertha,expertise(2,computing))],
researcher(mcelvey,bob,expertise(5,biology)),
researcher(pike,michelle,expertise(4,physics))).
group([researcher(davis,owen,expertise(4,mathematics)),
researcher(raleigh,sophie,expertise(4,physics))],
researcher(beattie,katy,expertise(5,engineering)),
researcher(deane,fergus,expertise(4,chemistry))).
group([researcher(hardy,dan,expertise(4,biology))],
researcher(mellon,paul,expertise(4,computing)),
researcher(halls,antonia,expertise(3,physics))).
group([researcher(doone,pat,expertise(2,computing)),
researcher(doone,burt,expertise(5,computing)),
researcher(doone,celia,expertise(4,computing)),
researcher(doone,norma,expertise(2,computing))],
researcher(maine,jack,expertise(3,biology)),
researcher(havilland,olive,expertise(5,chemistry))).
Given this information, write Prolog rules (and any additional predicates required) that can be used to return the following:
the first name and surname of any leader whose crew members number more than one and who all have the same surname. [4 marks]
This is the solution I presently have using recursion, though it's unnecessarily inefficient as for every member of the list, it compares that member to every other member. So, as the correct list is four members long, it returns 'jack maine' four times.
surname(researcher(S,_,_),S).
checkSurname([],Surname):-
Surname==Surname. % base case
checkSurname([Researcher|List],Surname):-
surname(Researcher,SameSurname),
Surname == SameSurname,
checkSurname(List,SameSurname).
q4(Forename,Surname):-
group(Crew,researcher(Surname,Forename,_),_),
length(Crew,Length),
Length > 1,
member(researcher(SameSurname,_,_),Crew),
checkSurname(Crew,SameSurname).
How could I do this without the duplicate results and without redundantly comparing each member to every other member each time? For every approach I've taken I am snagged each time with 'SameSurname' being left as a singleton, hence having to force use of it twice in the q4 predicate.
Current output
13 ?- q4(X,Y).
X = jack,
Y = maine ; x4
A compact and efficient solution:
q4(F, S) :-
group([researcher(First,_,_), researcher(Second,_,_)| Crew], researcher(S, F, _), _),
\+ (member(researcher(Surname, _, _), [researcher(Second,_,_)| Crew]), First \== Surname).
Example call (resulting in a single solution):
?- q4(X,Y).
X = jack,
Y = maine.
You are doing it more complicated than it has to be. Your q4/2 could be even simpler:
q4(First_name, Surname) :-
group(Crew, researcher(Surname, First_name, _E), _A),
length(Crew, Len), Len > 1,
all_same_surname(Crew).
Now you only need to define all_same_surname/1. The idea is simple: take the surname of the first crew member and compare it to the surnames of the rest:
all_same_surname([researcher(Surname, _FN, _E)|Rest]) :-
rest_same_surname(Rest, Surname).
rest_same_surname([], _Surname).
rest_same_surname([researcher(Surname, _FN, _E)|Rest), Surname) :-
rest_same_surname(Rest, Surname).
(Obviously, all_same_surname/1 fails immediately if there are no members of the crew)
This should be it, unless I misunderstood the problem statement.
?- q4(F, S).
F = jack,
S = maine.
How about that?
Note: The solution just takes the most straight-forward approach to answering the question and being easy to write and read. There is a lot of stuff that could be done otherwise. Since there is no reason not to, I used pattern matching and unification in the heads of the predicates, and not comparison in the body or extra predicates for extracting arguments from the compound terms.
P.S. Think about what member/2 does (look up its definition in the library, even), and you will see where all the extra choice points in your solution are coming from.
Boris did answer this question already, but I want to show the most concise solution I could come with. It's just for the educational purposes (promoting findall/3 and maplist/2):
q4(F, S) :-
group(Crew, researcher(S, F, _), _),
findall(Surname, member(researcher(Surname, _, _), Crew), Surnames),
Surnames = [ First, Second | Rest ],
maplist(=(First), [ Second | Rest ]).
I am trying to create a prolog rule which will generate all the people in a social network using S number degrees of separation.
This is the rule that i have made but it is only printing empty lists. Can somebody please help me into helping me understand why this is happening and me where i am going wrong?:
socialN(_,N):- N<1,!.
socialN(_,N,_,_):- N<1,!.
socialN(P1,Separation,S1,S):-
(message(P1,P2,_); message(P2,P1,_)),
D is Separation-1,
\+(member(P2,S1)),
append(P2,S1,S2),socialN(P1,D,S2,S),!.
socialN(P2,Separation,S,S).
These are the facts:
message(allan, steve, 2013-09-03).
message(nayna, jane, 2013-09-03).
message(steve, jane, 2013-09-04).
message(steve, allan, 2013-09-04).
message(mark, martin, 2013-09-04).
message(martin, steve, 2013-09-04).
message(allan, martin, 2013-09-05).
E.g. Mark’s network includes just Martin for 1 degree of separation; it includes Martin, Steve and Allan for 2 degrees of separation; and Martin, Steve, Allan and Jane for 3.
I see you are using append and member, so I suppose you are trying to build up a list of people. I was a bit surprised that you were not using findall. Like this:
allDirectLinks(P1, L) :- findall(P2, directlyLinked(P1, P2), L).
directlyLinked(P1, P1).
directlyLinked(P1, P2) :- message(P1, P2, _).
directlyLinked(P1, P2) :- message(P2, P1, _).
From there, you can write a recursive function to find the indirect links:
socialN(0, P, [P]) :- !.
socialN(N, P1, L3) :-
N>0, !,
N1 is N-1,
socialN(N1, P1, L1)
maplist(allDirectLinks, L1, L2),
append(L2, L3).
For example, this yields in Y a list of people separated 2 steps or less from Mark:
socialN(2, mark, X), list_to_set(X, Y).
Please note, Mark himself is included in the resulting list (being a 'level 0' link); I suppose it cannot be too hard to filter that out afterwards.
I hope this makes sense; I am a bit rusty, haven't done any Prolog in 25 years.
EDIT: explanation of the rules I defined:
directlyLinked: true if there is a message between two persons (regardless of the direction of the message)
allDirectLinks: accumulates into list L all persons directly linked to a given person P1; just read the manual about findall
socialN: builds up a list of people connected to a given person (P) at a distance less than or equal to a given distance (N)
socialN(0, ...): at distance 0, every person is linked to himself
socialN(N, ...): makes a recursive call to get a list of connections at distance N-1, then uses maplist to apply allDirectLinks to every connection found, and finally uses append to concatenate the results together.