Related
Say you have the following predicate:
random_int(X/Y):-
random(1,100,X),
random(1,100,Y),
X\=Y.
How can I populate a list of size n using the result of this predicate?
I tried the following code but it only populates the list if random_int(X) is true at the first attempt, i.e. it does not backtrack to try other combinations of X and Y.
findall(X,(between(1,N,_), random_int(X)),L).
I find this small 'application' of clpfd interesting:
?- N=10,M=12, repeat, findall(X, (between(1,N,_),random(1,M,X)), L), clpfd:all_different(L).
N = 10,
M = 12,
L = [5, 4, 6, 7, 9, 11, 2, 3, 8|...]
.
note: M must be > N
I guess a simple way to do it is to make a list of 1:100, and draw 100 times from it a sample of size 2, without replacement. Since this is Prolog and not R, you can instead do:
:- use_module(library(lists)).
:- use_module(library(random)).
random_pairs(Pairs) :-
findall(X/Y,
( between(1, 100, _),
randseq(2, 100, [X,Y])
), R).
This is available in SWI-Prolog at least, but it is free software and the source to randseq/3 is available on the web site.
And since it's better to not use findall unless strictly necessary, it would probable better to write:
random_pairs(Pairs) :-
length(Pairs, 100),
maplist(randseq(2, 100), Pairs).
or, if the X/Y is important,
random_pairs(Pairs) :-
length(Pairs, 100),
maplist(rand_couple(100), Pairs).
rand_couple(N, X/Y) :-
randseq(2, N, [X,Y]).
TL;DR Use the available libraries
You could do it with findall/3:
random_list(N, L) :-
findall(X, (between(1,N,_), random(50,100,X)), L).
Another tidy way to do this would be:
random_list(N, L) :-
length(L, N),
maplist(random(50, 100), L).
Which results in:
| ?- random_list(5, L).
L = [69,89,89,95,59]
yes
| ?-
In general, if you have a predicate, p(X1,X2,...,Xn,Y), and a list you want to fill with result Y using successive calls to p/(n+1), you can use length(List, Length) to set the length of your list, and then maplist(p(X1,...,Xn), List) to populate the list. Or, using the findall/3, you can do findall(X, (between(1,N,_), p(X1,...,Xn,X)), L)..
EDIT based upon the updated conditions of the question that the generated list be unique values...
The random predicates are not generators, so they don't create new random numbers on backtracking (either unique or otherwise). So this solution, likewise, will generate one list which meets the requirements, and then just succeed without generating more such lists on backtracking:
% Generate a random number X between A and B which is not in L
rand_not_in(A, B, L, X) :-
random(A, B, X1),
( memberchk(X1, L)
-> rand_not_in(A, B, L, X)
; X = X1
).
% Generate a list L of length N consisting of unique random numbers
% between A and B
random_list(N, L) :-
random_list(N, 50, 100, [], L).
random_list(N, A, B, Acc, L) :-
N > 0,
rand_not_in(A, B, A, X),
N1 is N - 1,
random_list(N1, A, B, [X|A], L).
random_list(0, _, _, L, L).
Yet another approach, in SWI Prolog, you can use randseq, which will give a random sequence in a range 1 to N. Just scale it:
random_list(N, A, B, L) :-
A < B,
Count is B - A + 1,
randseq(N, Count, L1),
Offset is A - 1,
maplist(offset(Offset), L1, L).
offset(X, Offset, Y) :-
Y is X + Offset.
?- random_list(5, 50, 100, L).
L = [54, 91, 90, 78, 75].
?-
random_len([],0).
random_len([Q|T],N) :-
random(1,100,Q),
random_len(T,X),
N is X+1.
I am new to Prolog and when I query
sortedUnion([1,1,1,2,3,4,4,5], [0,1,3,3,6,7], [0,1,2,3,4,5,6,7]).
I get an error
Exception: (7) unite([_G114, _G162, _G201, _G231, _G243], [_G249, _G297, _G336, _G357, _G369], [0, 1, 2, 3, 4, 5, 6, 7]) ?
So I am hoping someone will be able to tell me where my code is mistaken and why it is wrong?
%undup(L, U) holds precisely when U can be obtained from L by eliminating repeating occurrences of the same element
undup([], []).
undup([X|Xs], [_|B]) :- remove(X,Xs,K), undup(K, B).
remove(_,[],[]).
remove(Y,[Y|T],D) :- remove(Y,T,D).
remove(Y,[S|T],[S|R]) :- not(Y = S), remove(Y,T,R).
%sortedUnion(L1,L2,U) holds when U contains exactly one instance of each element
%of L1 and L2
sortedunion([H|T], [S|R], [F|B]) :- undup([H|T], N), undup([S|R], M), unite(N,M,[F|B]).
unite([], [], []).
unite([X], [], [X]).
unite([], [X], [X]).
unite([H|T], [S|R], [X|Xs]) :- S=H, X is S, unite(T, R, Xs).
unite([H|T], [S|R], [X|Xs]) :- H<S, X is H, unite(T, [S|R], Xs).
unite([H|T], [S|R], [X|Xs]) :- S<H, X is S, unite([H|T], R, Xs).
An advice first: try to keep your code as simple as possible. Your code can reduce to this (that surely works)
sortedunion(A, B, S) :-
append(A, B, C),
sort(C, S).
but of course it's instructive to attempt to solve by yourself. Anyway, try to avoid useless complications.
sortedunion(A, B, S) :-
undup(A, N),
undup(B, M),
unite(N, M, S).
it's equivalent to your code, just simpler, because A = [H|T] and so on.
Then test undup/2:
1 ?- undup([1,1,1,2,3,4,4,5],L).
L = [_G2760, _G2808, _G2847, _G2877, _G2889] ;
false.
Clearly, not what you expect. The culprit should that anon var. Indeed, this works:
undup([], []).
undup([X|Xs], [X|B]) :- remove(X,Xs,K), undup(K, B).
2 ?- undup([1,1,1,2,3,4,4,5],L).
L = [1, 2, 3, 4, 5] ;
false.
Now, unite/3. First of all, is/2 is abused. It introduces arithmetic, then plain unification suffices here: X = S.
Then the base cases are hardcoded to work where lists' length differs at most by 1. Again, simpler code should work better:
unite([], [], []).
unite( X, [], X).
unite([], X, X).
...
Also, note the first clause is useless, being already covered by (both) second and third clauses.
I was just introduced to Prolog and am trying to write a predicate that finds the Max value of a list of integers. I need to write one that compares from the beginning and the other that compares from the end. So far, I have:
max2([],R).
max2([X|Xs], R):- X > R, max2(Xs, X).
max2([X|Xs], R):- X <= R, max2(Xs, R).
I realize that R hasn't been initiated yet, so it's unable to make the comparison. Do i need 3 arguments in order to complete this?
my_max([], R, R). %end
my_max([X|Xs], WK, R):- X > WK, my_max(Xs, X, R). %WK is Carry about
my_max([X|Xs], WK, R):- X =< WK, my_max(Xs, WK, R).
my_max([X|Xs], R):- my_max(Xs, X, R). %start
other way
%max of list
max_l([X],X) :- !, true.
%max_l([X],X). %unuse cut
%max_l([X],X):- false.
max_l([X|Xs], M):- max_l(Xs, M), M >= X.
max_l([X|Xs], X):- max_l(Xs, M), X > M.
Ignoring the homework constraints about starting from the beginning or the end, the proper way to implement a predicate that gets the numeric maximum is as follows:
list_max([P|T], O) :- list_max(T, P, O).
list_max([], P, P).
list_max([H|T], P, O) :-
( H > P
-> list_max(T, H, O)
; list_max(T, P, O)).
A very simple approach (which starts from the beginning) is the following:
maxlist([],0).
maxlist([Head|Tail],Max) :-
maxlist(Tail,TailMax),
Head > TailMax,
Max is Head.
maxlist([Head|Tail],Max) :-
maxlist(Tail,TailMax),
Head =< TailMax,
Max is TailMax.
As you said, you must have the variables instantiated if you want to evaluate an arithmetic expression. To solve this, first you have to make the recursive call, and then you compare.
Hope it helps!
As an alternative to BLUEPIXY' answer, SWI-Prolog has a builtin predicate, max_list/2, that does the search for you. You could also consider a slower method, IMO useful to gain familiarity with more builtins and nondeterminism (and then backtracking):
slow_max(L, Max) :-
select(Max, L, Rest), \+ (member(E, Rest), E > Max).
yields
2 ?- slow_max([1,2,3,4,5,6,10,7,8],X).
X = 10 ;
false.
3 ?- slow_max([1,2,10,3,4,5,6,10,7,8],X).
X = 10 ;
X = 10 ;
false.
edit
Note you don't strictly need three arguments, but just to have properly instantiated variables to carry out the comparison. Then you can 'reverse' the flow of values:
max2([R], R).
max2([X|Xs], R):- max2(Xs, T), (X > T -> R = X ; R = T).
again, this is slower than the three arguments loops, suggested in other answers, because it will defeat 'tail recursion optimization'. Also, it does just find one of the maxima:
2 ?- max2([1,2,3,10,5,10,6],X).
X = 10 ;
false.
Here's how to do it with lambda expressions and meta-predicate foldl/4, and, optionally, clpfd:
:- use_module([library(lambda),library(apply),library(clpfd)]).
numbers_max([Z|Zs],Max) :- foldl(\X^S^M^(M is max(X,S)),Zs,Z,Max).
fdvars_max( [Z|Zs],Max) :- foldl(\X^S^M^(M #= max(X,S)),Zs,Z,Max).
Let's run some queries!
?- numbers_max([1,4,2,3],M). % integers: all are distinct
M = 4. % succeeds deterministically
?- fdvars_max( [1,4,2,3],M).
M = 4. % succeeds deterministically
?- numbers_max([1,4,2,3,4],M). % integers: M occurs twice
M = 4. % succeeds deterministically
?- fdvars_max( [1,4,2,3,4],M).
M = 4. % succeeds deterministically
What if the list is empty?
?- numbers_max([],M).
false.
?- fdvars_max( [],M).
false.
At last, some queries showing differences between numbers_max/2 and fdvars_max/2:
?- numbers_max([1,2,3,10.0],M). % ints + float
M = 10.0.
?- fdvars_max( [1,2,3,10.0],M). % ints + float
ERROR: Domain error: `clpfd_expression' expected, found `10.0'
?- numbers_max([A,B,C],M). % more general use
ERROR: is/2: Arguments are not sufficiently instantiated
?- fdvars_max( [A,B,C],M).
M#>=_X, M#>=C, M#=max(C,_X), _X#>=A, _X#>=B, _X#=max(B,A). % residual goals
list_max([L|Ls], Max) :- foldl(num_num_max, Ls, L, Max).
num_num_max(X, Y, Max) :- Max is max(X, Y).
%Query will be
?-list_max([4,12,5,3,8,90,10,11],Max).
Max=90
Right now I was working with recursion in Prolog, so if it is useful for someone I will leave 'my two cents' solving it in the two ways that I have thought:
% Start
start :- max_trad([2, 4, 6, 0, 5], MaxNumber1),
max_tail([2, 4, 6, 0, 5], 0, MaxNumber2),
show_results(MaxNumber1, MaxNumber2).
% Traditional Recursion (Method 1)
max_trad([Head|Tail], Max) :- max_trad(Tail, Value), Head > Value, Max is Head.
max_trad([Head|Tail], Max) :- max_trad(Tail, Value), Head =< Value, Max is Value.
max_trad([], 0).
% Tail Recursion (Method 2)
max_tail([], PartialMax, PartialMax).
max_tail([Head|Tail], PartialMax, FinalMax) :- Head > PartialMax, max_tail(Tail, Head, FinalMax).
max_tail([_|Tail], PartialMax, FinalMax) :- max_tail(Tail, PartialMax, FinalMax).
% Show both of the results
show_results(MaxNumber1, MaxNumber2) :-
write("The max value (obtained with traditional recursion) is: "), writeln(MaxNumber1),
write("The max value (obtained with tail recursion) is: "), writeln(MaxNumber2).
The output of the above code is:
Both methods are similar, the difference is that in the second an auxiliary variable is used in the recursion to pass values forward, while in the first method, although we have one less variable, we are filling the Stack with instructions to be executed later, so if it were an exaggeratedly large list, the second method is appropriate.
maximum_no([],Max):-
write("Maximum No From the List is:: ",Max).
maximum_no([H|T],Max):-
H>Max,
N = H,
maximum_no(T,N).
maximum_no(L,Max):-
maximum_no(L,Max).
The maximum number in a list in Prolog ?
max([],A):-print(A),!.
max([Head | Tail] , A):-A =< Head ,A1 is Head , max(Tail,A1) ; max(Tail,A).
max(L,M):-
member(M,L),
findall(X,(member(X,L),X>M),NL),
length(NL,0).
I am trying to calculate the Fibonacci series using the following function:
fib(0,A,_,A).
fib(N,A,B,F) :-
N1 is N-1, Sum is A+B, fib(N1, B, Sum, F).
fib(N, F) :- fib(N, 0, 1, F).
This is intended to works like this:
| ?- fib(20,Result).
Result = 6765 ?
But when I try this, it complains:
| ?- fib(What,6765).
uncaught exception: error(instantiation_error,(is)/2)
Does anyone understand why this is happening?
In the second clause:
fib(N,A,B,F) :-
N1 is N-1, Sum is A+B, fib(N1, B, Sum, F).
N is a variable to be decremented, and in your call to:
fib(What, 6765).
The variable is not yet defined, so you get the instantiation error on N1 is N - 1.
In swipl I do even get the error:
?- fib(W, 6765).
ERROR: fib/4: Arguments are not sufficiently instantiated
Now that you know it's an error, do you mind to know if it's actually possible to answer your query?
How do you would approach the problem? Your function it's ok, isn't it? Exactly, because it's a function, and not a relation, you get the error.
It's a bit complicate to solve it, but CLP can do !
See this fascinating example from CLP(FD) documentation (cited here)
:- use_module(library(clpfd)).
n_factorial(0, 1).
n_factorial(N, F) :-
N #> 0, N1 #= N - 1, F #= N * F1,
n_factorial(N1, F1).
We need something like this, but for fibonacci.
See how easy it is:
:- [library(clpfd)].
fib(0,A,_,A).
fib(N,A,B,F) :-
N #> 0,
N1 #= N-1,
Sum #= A+B,
fib(N1, B, Sum, F).
fib(N, F) :- fib(N, 0, 1, F).
i.e. replace is/2 by #=/2 and we get
?- fib(20,Result).
Result = 6765 .
?- fib(X,6765).
X = 20 ;
^C
note, after the first response the program loops!
Do you a see a way to correct it? Or another question could be worth...
A more clear and more natural predicate definition may be:
//The two base steps
fib1(0,0).
fib1(1,1).
//the recursive step
fib1(N,F) :-
N >= 0, M is N-2, O is N-1, fib1(M,A), fib1(O,B), F is A+B.
It is also a definition with only one predicate: fib/2
I have made two programs in Prolog for the nqueens puzzle using hill climbing and beam search algorithms.
Unfortunately I do not have the experience to check whether the programs are correct and I am in dead end.
I would appreciate if someone could help me out on that.
Unfortunately the program in hill climbing is incorrect. :(
The program in beam search is:
queens(N, Qs) :-
range(1, N, Ns),
queens(Ns, [], Qs).
range(N, N, [N]) :- !.
range(M, N, [M|Ns]) :-
M < N,
M1 is M+1,
range(M1, N, Ns).
queens([], Qs, Qs).
queens(UnplacedQs, SafeQs, Qs) :-
select(UnplacedQs, UnplacedQs1,Q),
not_attack(SafeQs, Q),
queens(UnplacedQs1, [Q|SafeQs], Qs).
not_attack(Xs, X) :-
not_attack(Xs, X, 1).
not_attack([], _, _) :- !.
not_attack([Y|Ys], X, N) :-
X =\= Y+N,
X =\= Y-N,
N1 is N+1,
not_attack(Ys, X, N1).
select([X|Xs], Xs, X).
select([Y|Ys], [Y|Zs], X) :- select(Ys, Zs, X).
I would like to mention this problem is a typical constraint satisfaction problem and can be efficiency solved using the CSP module of SWI-Prolog. Here is the full algorithm:
:- use_module(library(clpfd)).
queens(N, L) :-
N #> 0,
length(L, N),
L ins 1..N,
all_different(L),
applyConstraintOnDescDiag(L),
applyConstraintOnAscDiag(L),
label(L).
applyConstraintOnDescDiag([]) :- !.
applyConstraintOnDescDiag([H|T]) :-
insertConstraintOnDescDiag(H, T, 1),
applyConstraintOnDescDiag(T).
insertConstraintOnDescDiag(_, [], _) :- !.
insertConstraintOnDescDiag(X, [H|T], N) :-
H #\= X + N,
M is N + 1,
insertConstraintOnDescDiag(X, T, M).
applyConstraintOnAscDiag([]) :- !.
applyConstraintOnAscDiag([H|T]) :-
insertConstraintOnAscDiag(H, T, 1),
applyConstraintOnAscDiag(T).
insertConstraintOnAscDiag(_, [], _) :- !.
insertConstraintOnAscDiag(X, [H|T], N) :-
H #\= X - N,
M is N + 1,
insertConstraintOnAscDiag(X, T, M).
N is the number of queens or the size of the board (), and , where , being the position of the queen on the line .
Let's details each part of the algorithm above to understand what happens.
:- use_module(library(clpfd)).
It indicates to SWI-Prolog to load the module containing the predicates for constraint satisfaction problems.
queens(N, L) :-
N #> 0,
length(L, N),
L ins 1..N,
all_different(L),
applyConstraintOnDescDiag(L),
applyConstraintOnAscDiag(L),
label(L).
The queens predicate is the entry point of the algorithm and checks if the terms are properly formatted (number range, length of the list). It checks if the queens are on different lines as well.
applyConstraintOnDescDiag([]) :- !.
applyConstraintOnDescDiag([H|T]) :-
insertConstraintOnDescDiag(H, T, 1),
applyConstraintOnDescDiag(T).
insertConstraintOnDescDiag(_, [], _) :- !.
insertConstraintOnDescDiag(X, [H|T], N) :-
H #\= X + N,
M is N + 1,
insertConstraintOnDescDiag(X, T, M).
It checks if there is a queen on the descendant diagonal of the current queen that is iterated.
applyConstraintOnAscDiag([]) :- !.
applyConstraintOnAscDiag([H|T]) :-
insertConstraintOnAscDiag(H, T, 1),
applyConstraintOnAscDiag(T).
insertConstraintOnAscDiag(_, [], _) :- !.
insertConstraintOnAscDiag(X, [H|T], N) :-
H #\= X - N,
M is N + 1,
insertConstraintOnAscDiag(X, T, M).
Same as previous, but it checks if there is a queen on the ascendant diagonal.
Finally, the results can be found by calling the predicate queens/2, such as:
?- findall(X, queens(4, X), L).
L = [[2, 4, 1, 3], [3, 1, 4, 2]]
If I read your code correctly, the algorithm you're trying to implement is a simple depth-first search rather than beam search. That's ok, because it should be (I don't see how beam search will be effective for this problem and it can be hard to program).
I'm not going to debug this code for you, but I will give you a suggestion: build the chess board bottom-up with
queens(0, []).
queens(N, [Q|Qs]) :-
M is N-1,
queens(M, Qs),
between(1, N, Q),
safe(Q, Qs).
where safe(Q,Qs) is true iff none of Qs attack Q. safe/2 is then the conjunction of a simple memberchk/2 check (see SWI-Prolog manual) and your not_attack/2 predicate, which on first sight seems to be correct.
A quick check on Google has found a few candidates for you to compare with your code and find what to change.
My favoured solution for sheer clarity would be the second of the ones linked to above:
% This program finds a solution to the 8 queens problem. That is, the problem of placing 8
% queens on an 8x8 chessboard so that no two queens attack each other. The prototype
% board is passed in as a list with the rows instantiated from 1 to 8, and a corresponding
% variable for each column. The Prolog program instantiates those column variables as it
% finds the solution.
% Programmed by Ron Danielson, from an idea by Ivan Bratko.
% 2/17/00
queens([]). % when place queen in empty list, solution found
queens([ Row/Col | Rest]) :- % otherwise, for each row
queens(Rest), % place a queen in each higher numbered row
member(Col, [1,2,3,4,5,6,7,8]), % pick one of the possible column positions
safe( Row/Col, Rest). % and see if that is a safe position
% if not, fail back and try another column, until
% the columns are all tried, when fail back to
% previous row
safe(Anything, []). % the empty board is always safe
safe(Row/Col, [Row1/Col1 | Rest]) :- % see if attack the queen in next row down
Col =\= Col1, % same column?
Col1 - Col =\= Row1 - Row, % check diagonal
Col1 - Col =\= Row - Row1,
safe(Row/Col, Rest). % no attack on next row, try the rest of board
member(X, [X | Tail]). % member will pick successive column values
member(X, [Head | Tail]) :-
member(X, Tail).
board([1/C1, 2/C2, 3/C3, 4/C4, 5/C5, 6/C6, 7/C7, 8/C8]). % prototype board
The final link, however, solves it in three different ways so you can compare against three known solutions.