I have the following predicate execute(actualState, instruction, nextState):-
such that when executing with the instructions: move, swap , i have the following solutions:
?- executed(regs(1,4,*,+,2), swap(1,2), NS).
solution:
NS = regs(4,1,*,+,2)?;
no
?- executed(regs(1,4,3,6,+), move(4), NS).
solution:
NS = regs(1,4,3,6,6)?;
no
How can I implement it?
what I want it to do is that it has an initial state, an instruction and a final state "executed (actualState, instruction, nextState)" and what I want to do is pass it a list of registers as initial state, for example "regs (1,2,3,4)" and an instruction, for example, move and swap. swap (swap the position X, X + 1) and move (copy what is in X and deposit it in X + 1) and what I want it to return, as final state, are the examples described in the statement of my question.
I would take the following approach. The key elements of this solution are:
Use of nth1/3 for considering an element of a list at a specified position
=../2 for mapping between a term with arguments and a list
A "substitution" predicate that substitutes a value at specified position in a list with another
subst([_|T], Y, 1, [Y|T]).
subst([X|T], Y, N, [X|T1]) :-
N #> 1,
N1 #= N - 1,
subst(T, Y, N1, T1).
executed(AS, swap(X,Y), NS) :-
AS =.. [regs|P],
nth1(X, P, Xe),
nth1(Y, P, Ye),
subst(P, Ye, X, P1),
subst(P1, Xe, Y, P2),
NS =.. [regs|P2].
executed(AS, move(X), NS) :-
AS =.. [regs|P],
nth1(X, P, Xe),
X1 #= X + 1,
subst(P, Xe, X1, P1),
NS =.. [regs|P1].
If you are using SWI prolog, you'll need to include the clpfd library, :- use_module(library(clpfd)).. Also some Prologs, such as Ciao Prolog, does not have nth1/3. Ciao does provide, however, nth/3 which has the same behavior, so it may be substituted.
Note that I'm using CLP(FD) here for more generality. If your system doesn't support CLP(FD) you can use is in place of #=, although it's less desirable.
Note that this solution works as long as the arguments indexing the registers are "in range". So it will fail on executed(regs(1,2,+), move(3), NS).. As an exercise, if this is required, you should try to enhance this solution to meet that need. It will help you to learn Prolog versus being given every detail of the solution.
Here is a solution of swap. The key is term to list =...
The rest is to dissect the list and put it back together.
Move is a piece of cake based on this answer and I left it "as an exercise"
:- use_module(library(lists)).
executed(H,swap(X,Y),Result):-
H =.. [regs|TH],
LL1 is X-1,
LL2 is Y-X-1,
length(TH,LL),
LL3 is LL-Y,
length(L1,LL1),
length(L2,LL2),
length(L3,LL3),
append(L1,LI1,TH),[EX|LIX]=LI1,append(L2,LI2,LIX),[EY|L3]=LI2,
flatten([regs,L1,EY,L2,EX,L3],LR),
Result =.. LR.
Related
I like the idea of lazy_findall as it helps me with keeping predicates separated and hence program decomposition.
What are the cons of using lazy_findall and are there alternatives?
Below is my "coroutine" version of the branch and bound problem.
It starts with the problem setup:
domain([[a1, a2, a3],
[b1, b2, b3, b4],
[c1, c2]]).
price(a1, 1900).
price(a2, 750).
price(a3, 900).
price(b1, 300).
price(b2, 500).
price(b3, 450).
price(b4, 600).
price(c1, 700).
price(c2, 850).
incompatible(a2, c1).
incompatible(b2, c2).
incompatible(b3, c2).
incompatible(a2, b4).
incompatible(a1, b3).
incompatible(a3, b3).
Derived predicates:
all_compatible(_, []).
all_compatible(X, [Y|_]) :- incompatible(X, Y), !, fail.
all_compatible(X, [_|T]) :- all_compatible(X, T).
list_price(A, Threshold, P) :- list_price(A, Threshold, 0, P).
list_price([], _, P, P).
list_price([H|T], Threshold, P0, P) :-
price(H, P1),
P2 is P0 + P1,
P2 =< Threshold,
list_price(T, Threshold, P2, P).
path([], []).
path([H|T], [I|Q]) :-
member(I, H),
path(T, Q),
all_compatible(I, Q).
The actual logic:
solution([], Paths, Paths, Value, Value).
solution([C|D], Paths0, Paths, Value0, Value) :-
( list_price(C, Value0, V)
-> ( V < Value0
-> solution(D, [C], Paths, V, Value)
; solution(D, [C|Paths0], Paths, Value0, Value)
)
; solution(D, Paths0, Paths, Value0, Value)
).
The glue
solution(Paths, Value) :-
domain(D),
lazy_findall(P, path(D, P), Paths0),
solution(Paths0, [], Paths, 5000, Value).
Here is an alternative no-lazy-findall solution by #gusbro: https://stackoverflow.com/a/68415760/1646086
I am not familiar with lazy_findall but I observe two "drawbacks" with the presented approach:
The code is not as decoupled as one might want, because there is still a mix of "declarative" and "procedural" code in the same predicate. I am putting quotes around the terms because they can mean a lot of things but here I see that path/2 is concerned with both generating paths AND ensuring that they are valid. Similarly solution/5 (or rather list_price/3-4) is concerned with both computing the cost of paths and eliminating too costly ones with respect to some operational bound.
The "bounding" test only happens on complete paths. This means that in practice all paths are generated and verified in order to find the shortest one. It does not matter for such a small problem but might be important for larger instances. Ideally, one might want to detect for instance that the partial path [a1,?,?] will never bring a solution less than 2900 without trying all values for b and c.
My suggestion is to instead use clpfd (or clpz, depending on your system) to solve both issues. With clpfd, one can first state the problem without concern for how to solve it, then call a predefined predicate (like labeling/2) to solve the problem in a (hopefully) clever way.
Here is an example of code that starts from the same "setup" predicates as in the question.
state(Xs,Total):-
domain(Ds),
init_vars(Ds,Xs,Total),
post_comp(Ds,Xs).
init_vars([],[],0).
init_vars([D|Ds],[X|Xs],Total):-
prices(D,P),
length(D,N),
X in 1..N,
element(X, P, C),
Total #= C + Total0,
init_vars(Ds,Xs,Total0).
prices([],[]).
prices([V|Vs],[P|Ps]):-
price(V,P),
prices(Vs,Ps).
post_comp([],[]).
post_comp([D|Ds],[X|Xs]):-
post_comp0(Ds,D,Xs,X),
post_comp(Ds,Xs).
post_comp0([],_,[],_).
post_comp0([D2|Ds],D1,[X2|Xs],X1):-
post_comp1(D1,1,D2,X1,X2),
post_comp0(Ds,D1,Xs,X1).
post_comp1([],_,_,_,_).
post_comp1([V1|Vs1],N,Vs2,X1,X2):-
post_comp2(Vs2,1,V1,N,X2,X1),
N1 is N+1,
post_comp1(Vs1,N1,Vs2,X1,X2).
post_comp2([],_,_,_,_,_).
post_comp2([V2|Vs2],N2,V1,N1,X2,X1):-
post_comp3(V2,N2,X2,V1,N1,X1),
N3 is N2 + 1,
post_comp2(Vs2,N3,V1,N1,X2,X1).
post_comp3(V2,N2,X2,V1,N1,X1) :-
( ( incompatible(V2,V1)
; incompatible(V1,V2)
)
-> X2 #\= N2 #\/ X1 #\= N1
; true
).
Note that the code is relatively straightforward, except for the (quadruple) loop to post the incompatibility constraints. This is due to the way I wanted to reuse the predicates in the question. In practice, one might want to change the way the data is presented.
The problem can then be solved with the following query (in SWI-prolog):
?- state(Xs, T), labeling([min(T)], Xs).
T = 1900, Xs = [2, 1, 2] ?
In SICStus prolog, one can write instead:
?- state(Xs, T), minimize(labeling([], Xs), T).
Xs = [2,1,2], T = 1900 ?
Another short predicate could then transform back the [2,1,2] list into [a2,b1,c2] if that format was expected.
I wrote a test program with bindings (facts) between atoms and numbers.
bind(a, 3).
bind(b, 4).
bind(c, 5).
As part of a toy interpreter, I want to be able to perform additions on these atoms using Prolog's native arithmetic operators. For instance, I want to be able to run this query:
% val(X) is the value bound to X
?- X is val(a) + val(b).
X = 7.
However, I'm struggling to find a way to allow this addition. My first approach would have been this one:
% val(X, Y): Y is the value bound to X
val(X, Y) :- bind(X, Y).
% Make val an arithmetic function
:- arithmetic_function(val/1).
However, arithmetic_function/1 is no longer part of Prolog (or at least SWI-Prolog says it's deprecated), so I can't use it. Then I believed the best solution would be to overload the + operator to take this into account:
% val(X, Y): Y is the value bound to X
val(val(X), Y) :- bind(X, Y).
% Overload the + operator
+(val(_X, XVal), val(_Y, YVal)) :- XVal + YVal.
But here I've got my syntax all messed up because I don't really know how to overload a native arithmetic operation. When I type in the sample query from before, SWI-Prolog says ERROR: Arithmetic: ``val(a)' is not a function.
Would you have hints about a possible solution or a better approach or something I missed?
From the docs, I tought you should use function_expansion/3.
But I'm unable to get it to work, instead, goal_expansion could do, but isn't very attractive... for instance, if you save the following definitions in a file bind.pl (just to say)
:- module(bind, [test/0]).
:- dynamic bind/2.
bind(a, 3).
bind(b, 4).
bind(c, 5).
% :- multifile user:goal_expansion/2.
user:goal_expansion(val(X), Y) :- bind(X, Y).
user:goal_expansion(X is Y, X is Z) :- expand_goal(Y, Z).
user:goal_expansion(X + Y, U + V) :- expand_goal(X, U), expand_goal(Y, V).
test :-
X is val(a) + val(b), writeln(X).
and consult it, you can run your test:
?- test.
7
edit
after Paulo suggestion, here is an enhanced solution, that should work for every binary expression.
user:goal_expansion(X is Y, X is Z) :- expr_bind(Y, Z).
expr_bind(val(A), V) :- !, bind(A, V).
expr_bind(X, Y) :-
X =.. [F, L, R], % get operator F and Left,Right expressions
expr_bind(L, S), % bind Left expression
expr_bind(R, T), % bind Right expression
Y =.. [F, S, T]. % pack bound expressions back with same operator
expr_bind(X, X). % oops, I forgot... this clause allows numbers and variables
having defined user as target module for goal_expansion, it works on the CLI:
?- R is val(a)*val(b)-val(c).
R = 7.
edit
now, let's generalize to some other arithmetic operators, using the same skeleton expr_bind uses for binary expressions:
user:goal_expansion(X, Y) :-
X =.. [F,L,R], memberchk(F, [is, =<, <, =:=, >, >=]),
expr_bind(L, S),
expr_bind(R, T),
Y =.. [F, S, T].
and unary operators (I cannot recall no one apart minus, so I show a simpler way than (=..)/2):
...
expr_bind(-X, -Y) :- expr_bind(X, Y).
expr_bind(X, X).
Now we get
?- -val(a)*2 < val(b)-val(c).
true.
One way to do it is using Logtalk parametric objects (Logtalk runs on SWI-Prolog and 11 other Prolog systems; this makes this solution highly portable). The idea is to define each arithmetic operation as a parametric object that understands an eval/1 message. First we define a protocol that will be implemented by the objects representing the arithmetic operations:
:- protocol(eval).
:- public(eval/1).
:- end_protocol.
The basic parametric object understands val/1 and contains the bind/2 table:
:- object(val(_X_), implements(eval)).
eval(X) :-
bind(_X_, X).
bind(a, 3).
bind(b, 4).
bind(c, 5).
:- end_object.
I exemplify here only the implementation for arithmetic addition:
:- object(_X_ + _Y_, implements(eval)).
eval(Result) :-
_X_::eval(X), _Y_::eval(Y),
Result is X + Y.
:- end_object.
Sample call (assuming the entities above are saved in an eval.lgt file):
% swilgt
...
?- {eval}.
% [ /Users/pmoura/Desktop/eval.lgt loaded ]
% (0 warnings)
true.
?- (val(a) + val(b))::eval(R).
R = 7.
This can be an interesting solution if you plan to implement more functionality other than expression evaluation. E.g. a similar solution but for symbolic differentiation of arithmetic expressions can be found at:
https://github.com/LogtalkDotOrg/logtalk3/tree/master/examples/symdiff
This solution will also work in the case of runtime generated expressions (term-expansion based solutions usually only work at source file compile time and at the top-level).
If you're only interested in expression evaluation, Capelli's solution is more compact and retains is/2 for evaluation. It can also be made more portable if necessary using Logtalk's portable term-expansion mechanism (but note the caveat in the previous paragraph).
This is perhaps not exactly what I was looking for, but I had an idea:
compute(val(X) + val(Y), Out) :-
bind(X, XVal),
bind(Y, YVal),
Out is XVal + YVal.
Now I can run the following query:
?- compute(val(a) + val(c), Out).
Out = 8.
Now I need to define compute for every arithmetic operation I'm interested in, then get my interpreter to run expressions through it.
I want to write predicate which can count all encountered number:
count(1, [1,0,0,1,0], X).
X = 2.
I tried to write it like:
count(_, [], 0).
count(Num, [H|T], X) :- count(Num, T, X1), Num = H, X is X1 + 1.
Why doesn't work it?
Why doesn't work it?
Prolog is a programming language that often can answer such question directly. Look how I tried out your definition starting with your failing query:
?- count(1, [1,0,0,1,0], X).
false.
?- count(1, Xs, X).
Xs = [], X = 0
; Xs = [1], X = 1
; Xs = [1,1], X = 2
; Xs = [1,1,1], X = 3
; ... .
?- Xs = [_,_,_], count(1, Xs, X).
Xs = [1,1,1], X = 3.
So first I realized that the query does not work at all, then I generalized the query. I replaced the big list by a variable Xs and said: Prolog, fill in the blanks for me! And Prolog did this and reveals us precisely the cases when it will succeed.
In fact, it only succeeds with lists of 1s only. That is odd. Your definition is too restricted - it correctly counts the 1s in lists where there are only ones, but all other lists are rejected. #coder showed you how to extend your definition.
Here is another one using library(reif) for
SICStus|SWI. Alternatively, see tfilter/3.
count(X, Xs, N) :-
tfilter(=(X), Xs, Ys),
length(Ys, N).
A definition more in the style of the other definitions:
count(_, [], 0).
count(E, [X|Xs], N0) :-
if_(E = X, C = 1, C = 0),
count(E, Xs, N1),
N0 is N1+C.
And now for some more general uses:
How does a four element list look like that has 3 times a 1 in it?
?- length(L, 4), count(1, L, 3).
L = [1,1,1,_A], dif(1,_A)
; L = [1,1,_A,1], dif(1,_A)
; L = [1,_A,1,1], dif(1,_A)
; L = [_A,1,1,1], dif(1,_A)
; false.
So the remaining element must be something different from 1.
That's the fine generality Prolog offers us.
The problem is that as stated by #lurker if condition (or better unification) fails then the predicate will fail. You could make another clause for this purpose, using dif/2 which is pure and defined in the iso:
count(_, [], 0).
count(Num, [H|T], X) :- dif(Num,H), count(Num, T, X).
count(Num, [H|T], X) :- Num = H, count(Num, T, X1), X is X1 + 1.
The above is not the most efficient solution since it leaves many choice points but it is a quick and correct solution.
You simply let the predicate fail at the unification Num = X. Basically, it's like you don't accept terms which are different from the only one you are counting.
I propose to you this simple solution which uses tail recursion and scans the list in linear time. Despite the length, it's very efficient and elegant, it exploits declarative programming techniques and the backtracking of the Prolog engine.
count(C, L, R) :-
count(C, L, 0, R).
count(_, [], Acc, Acc).
count(C, [C|Xr], Acc, R) :-
IncAcc is Acc + 1,
count(C, Xr, IncAcc, R).
count(C, [X|Xr], Acc, R) :-
dif(X, C),
count(C, Xr, Acc, R).
count/3 is the launcher predicate. It takes the term to count, the list and gives to you the result value.
The first count/4 is the basic case of the recursion.
The second count/4 is executed when the head of the list is unified with the term you are looking for.
The third count/4 is reached upon backtracking: If the term doesn’t match, the unification fails, you won't need to increment the accumulator.
Acc allows you to scan the entire list propagating the partial result of the recursive processing. At the end you simply have to return it.
I solved it myself:
count(_, [], 0).
count(Num, [H|T], X) :- Num \= H, count(Num, T, X).
count(Num, [H|T], X) :- Num = H, count(Num, T, X1), X is X1 + 1.
I have decided to add my solution to the list here.
Other solutions here use either explicit unification/failure to unify, or libraries/other functions, but mine uses cuts and implicit unification instead. Note my solution is similar to Ilario's solution but simplifies this using cuts.
count(_, [], 0) :- !.
count(Value, [Value|Tail],Occurrences) :- !,
count(Value,Tail,TailOcc),
Occurrences is TailOcc+1.
count(Value, [_|Tail], Occurrences) :- count(Value,Tail,Occurrences).
How does this work? And how did you code it?
It is often useful to equate solving a problem like this to solving a proof by induction, with a base case, and then a inductive step which shows how to reduce the problem down.
Line 1 - base case
Line 1 (count(_, [], 0) :- !.) handles the "base case".
As we are working on a list, and have to look at each element, the simplest case is zero elements ([]). Therefore, we want a list with zero elements to have no instances of the Value we are looking for.
Note I have replaced Value in the final code with _ - this is because we do not care what value we are looking for if there are no values in the list anyway! Therefore, to avoid a singleton variable we negate it here.
I also added a ! (a cut) after this - as there is only one correct value for the number of occurrences we do not want Prolog to backtrack and fail - therefore we tell Prolog we found the correct value by adding this cut.
Lines 2/3 - inductive step
Lines 2 and 3 handle the "inductive step". This should handle if we have one or more elements in the list we are given. In Prolog we can only directly look at the head of the list, therefore let us look at one element at a time. Therefore, we have two cases - either the value at the head of the list is the Value we are looking for, or it is not.
Line 2
Line 2 (count(Value, [Value|Tail],Occurrences) :- !, count(Value,Tail,TailOcc), Occurrences is TailOcc+1.) handles if the head of our list and the value we are looking for match. Therefore, we simply use the same variable name so Prolog will unify them.
A cut is used as the first step in our solution (which makes each case mutually exclusive, and makes our solution last-call-optimised, by telling Prolog not to try any other rules).
Then, we find out how many instances of our term there are in the rest of the list (call it TailOcc). We don't know how many terms there are in the list we have at the moment, but we know it is one more than there are in the rest of the list (as we have a match).
Once we know how many instances there are in the rest of the list (call this Tail), we can take this value and add 1 to it, then return this as the last value in our count function (call this Occurences).
Line 3
Line 3 (count(Value, [_|Tail], Occurrences) :- count(Value,Tail,Occurrences).) handles if the head of our list and the value we are looking for do not match.
As we used a cut in line 2, this line will only be tried if line 2 fails (i.e. there is no match).
We simply take the number of instances in the rest of the list (the tail) and return this same value without editing it.
I've been searching for something that might help me with my problem all over the internet but I haven't been able to make any progress. I'm new to logic programming and English is not my first language so apologize for any mistake.
Basically I want to implement this prolog program: discord/3 which has arguments L1, L2 lists and P where P are the indexes of the lists where L1[P] != L2[P] (in Java). In case of different lengths, the not paired indexes just fail. Mode is (+,+,-) nondet.
I got down the basic case but I can't seem to wrap my head around on how to define P in the recursive call.
discord(_X,[],_Y) :-
fail.
discord([H1|T1],[H1|T2],Y) :-
???
discord(T1,T2,Z).
discord([_|T1],[_|T2],Y) :-
???
discord(T1,T2,Z).
The two clauses above are what I came up to but I have no idea on how to represent Y - and Z - so that the function actually remembers the length of the original list. I've been thinking about using nth/3 with eventually an assert but I'm not sure where to place them in the program.
I'm sure there has to be an easier solution although. Thanks in advance!
You can approach this in two ways. First, the more declarative way would be to enumerate the indexed elements of both lists with nth1/3 and use dif/2 to ensure that the two elements are different:
?- L1 = [a,b,c,d],
L2 = [x,b,y,d],
dif(X, Y),
nth1(P, L1, X),
nth1(P, L2, Y).
X = a, Y = x, P = 1 ;
X = c, Y = y, P = 3 ;
false.
You could also attempt to go through both list at the same time and keep a counter:
discord(L1, L2, P) :-
discord(L1, L2, 1, P).
discord([X|_], [Y|_], P, P) :-
dif(X, Y).
discord([_|Xs], [_|Ys], N, P) :-
succ(N, N1),
discord(Xs, Ys, N1, P).
Then, from the top level:
?- discord([a,b,c,d], [a,x,c,y], Ps).
Ps = 2 ;
Ps = 4 ;
false.
I have a knowledge base that consists of students database in a file 'students.pl' like this:
% student(Name,Percent,List_of_Marks_in_3_subjects).
student('abc',83,[80,80,90]).
student('pqr',70,[70,60,80]).
student('xyz',76,[80,70,80]).
I want to access each student predicate from the knowledge base and calculate the average marks in each subject or average percentage, without using 'findall' or assert/retract.
I may want to use backtracking like this:
find_score_all(X) :- student(Name,Percent,L),
write(Percent),nl,
fail.
find_score_all(_).
With this approach I can access each element and write it, but if I want to add each 'Percent' value as an element to a list or just use a predicate like 'Percent1 is Total + Percent' to total the percent values and then find its average, how can I do so?
Note that I dont want to use findall or retract/assert and preferably find the average in one pass through the knowledge base since the knowledge base is very large.
Any help is appreciated.
%solution for sum of percents, you can replace with any other calculation sum_percent predicate.
listing(student/3, convert_to_list/2, sum_percent, sum_percent/2).
% student(Name,Percent,List_of_Marks_in_3_subjects).
student('abc',83,[80,80,90]).
student('pqr',70,[70,60,80]).
student('xyz',76,[80,70,80]).
convert_to_list(X, R):-
student(N, P, LM),
not(member(st(N, P, LM), X)),
convert_to_list([st(N, P, LM)|X], R).
convert_to_list(X, X).
sum_percent:-
convert_to_list([], X),
sum_percent(X, S),
write(S).
sum_percent([], 0).
sum_percent([st(_,E,_)|T], S):-
sum_percent(T, S2),
S is E+S2.
if you want to add to a list then you should use findall, or better, library(aggregate). But if you fear about efficiency, you could use something like this
integrate(ave, Goal, Ave) :-
State = state(0, 0, _),
repeat,
( call(Goal, V),
arg(1, State, C), U is C+1, nb_setarg(1, State, U),
arg(2, State, S), T is S+V, nb_setarg(2, State, T),
fail
; arg(1, State, C), arg(2, State, S), Ave is S/C
).
:- meta_predicate integrate(+, :, ?).
test:
members(X) :- member(X, [1,2,3,4]).
?- integrate(ave, members, R).
R = 2.5 .
Of course, you'll need to add error handling (at least, when counter C == 0).