Related
subtrees([]).
subtrees([(Cost,T)|Rest]) :−
number(Cost),
istree(T),
subtrees(Rest).
istree(tree(_,Children)) :− subtrees(Children).
dfs(GoalValue,tree(GoalValue,_),GoalValue,0).
dfs(GoalValue,tree(Value,[(Cost,T)|Rest]),Path,FinalCost) :−
T = tree(IV,_),
write(IV ),
dfs(GoalValue, T,P,C),
string_concat(Value,P,Path),
FinalCost is C+Cost
; % go down one depth level
dfs(GoalValue,tree(Value,Rest),Path,FinalCost). % next child
Can someone help me understand this Prolog implementation of Depth First Search? A subpart of my question also includes how to interpret splitting within the Head part.
subtrees([(Cost,T)|Rest])
I am aware that each list is considered [Heads|Tails], but how does one interpret (Cost, T )? Is it a 2D list?
The builtin predicate write_canonical/1 is very useful for interpreting terms as it will remove syntactic sugar. So for your query:
?- write_canonical(subtrees([(Cost,T)|Rest])).
subtrees('.'(','(Cost, T), Rest)).
This means you have a subtrees/1 predicate that contains a list (a list without syntactic sugar is: '.'(Head, Tail)). The first element of that list is the term ','(Cost, T):
?- write_canonical((Cost, T)).
','(Cost, T)
This kind of ','/2 term is actually a Prolog conjunctive clause. It appears the author is abusing the homoiconic nature of Prolog here to mimic a tuple, which becomes inefficient for "tuples" with a length greater than 2 ((a, b, c) is actually ','(a, ',',(b, c)); better with an unnested term like f(a, b, c)), and so is best to avoid. The reading of (Cost, T) is "Cost and T".
Hello good people of programming .
Logic programming is always fascinating compare to imperative programming.
As pursuing unknown of logic programming, there is some problems encountering arithmetic expressions.
Here is the code I have done so far.
number_atom(N) :-
(number(N) -> functor(N, _, _); functor(N, _, _), atom(N)).
arithmeticAdd_expression(V,V,Val,Val).
arithmeticAdd_expression(N, _Var, _Val, N) :-
number_atom(N).
arithmeticAdd_expression(X+Y, Var, Val, R) :-
arithmeticAdd_expression(X, Var, Val, RX),
arithmeticAdd_expression(Y, Var, Val, RY),
(number(RX), number(RY) -> R is RX + RY; R = RX + RY).
Taking add operation as example:
arithmeticAdd_expression(Expression, Variable, Value, Result)
?- arithmeticAdd_expression(a+10, a, 1, Result).
?- Result = 11;
?- Result = a + 10.
?- arithmeticAdd_expression(a+10, b, 1, Result).
?- Result = a + 10.
What I would like to achieve is that
if the atom(s) in the Expression can only be substituted by given Variable and value, then Result is the number only like the example shown above(Result = 11). Else, the Result is the Expression itself only. My problem with the code is somewhere there, I just could figure it out. So, Please someone can help me? Thank you.
An important attraction of logic programming over, say, functional programming is that you can often use the same code in multiple directions.
This means that you can ask not only for a particular result if the inputs are given, but also ask how solutions look like in general.
However, for this to work, you have to put some thought into the way you represent your data. For example, in your case, any term in your expression that is still a logical variable may denote either a given number or an atom that should be interpreted differently than a plain number or an addition of two other terms. This is called a defaulty representation because you have to decide what a variable should denote by default, and there is no way to restrict its meaning to only one of the possible cases.
Therefore, I suggest first of all to change the representation so that you can symbolically distinguish the two cases. For example, to represent expressions in your case, let us adopt the convention that:
atoms are denoted by the wrapper a/1
numbers are denoted by the wrapper n/1.
and as is already the case, (+)/2 shall denote addition of two expressions.
So, a defaulty term like b+10 shall now be written as: a(b)+n(10). Note the use of the wrappers a/1 and n/1 to make clear which case we are dealing with. Such a representation is called clean. The wrappers are arbitrarily (though mnemonically) chosen, and we could have used completely different wrappers such as atom/1 and number/1, or atm/1 and nmb/1. The key property is only that we can now symbolically distinguish different cases by virtue of their outermost functor and arity.
Now the key advantage: Using such a convention, we can write for example: a(X)+n(Y). This is a generalization of the earlier term. However, it carries a lot more information than only X+Y, because in the latter case, we have lost track of what these variables stand for, while in the former case, this distinction is still available.
Now, assuming that this convention is used in expressions, it becomes straight-forward to describe the different cases:
expression_result(n(N), _, _, n(N)).
expression_result(a(A), A, N, n(N)).
expression_result(a(A), Var, _, a(A)) :-
dif(A, Var).
expression_result(X+Y, Var, Val, R) :-
expression_result(X, Var, Val, RX),
expression_result(Y, Var, Val, RY),
addition(RX, RY, R).
addition(n(X), n(Y), n(Z)) :- Z #= X + Y.
addition(a(X), Y, a(X)+Y).
addition(X, a(Y), X+a(Y)).
Note that we can now use pattern matching to distinguish the cases. No more if-then-elses, and no more atom/1 or number/1 tests are necessary.
Your test cases work as expected:
?- expression_result(a(a)+n(10), a, 1, Result).
Result = n(11) ;
false.
?- expression_result(a(a)+n(10), b, 1, Result).
Result = a(a)+n(10) ;
false.
And now the key advantage: With such a pure program (please see logical-purity for more information), we can also ask "What do results look like in general?"
?- expression_result(Expr, Var, N, R).
Expr = R, R = n(_1174) ;
Expr = a(Var),
R = n(N) ;
Expr = R, R = a(_1698),
dif(_1698, Var) ;
Expr = n(_1852)+n(_1856),
R = n(_1896),
_1852+_1856#=_1896 ;
Expr = n(_2090)+a(Var),
R = n(_2134),
_2090+N#=_2134 .
Here, I have used logical variables for all arguments, and I get quite general answers from this program. This is why I have used clpfd constraints for declarative integer arithmetic.
Thus, your immediate issue can be readily solved by using a clean representation, and using the code above.
Only one very small challenge remains: Maybe you actually want to use a defaulty representation such as c+10 (instead of a(c)+n(10)). The task you are then facing is to convert the defaulty representation to a clean one, for example via a predicate defaulty_clean/2. I leave this as an easy exercise. Once you have a clean representation, you can use the code above without changes.
I am new to prolog, I am just learning about lists and I came across this question. The answer works perfect for a list of integers.
minimo([X], X) :- !.
minimo([X,Y|Tail], N):-
( X > Y ->
minimo([Y|Tail], N)
;
minimo([X|Tail], N)
).
How can I change this code to get the smallest int from a mixed list?
This
sint([a,b,3,2,1],S)
should give an answer:
S=1
you could just ignore the problem, changing the comparison operator (>)/2 (a binary builtin predicate, actually) to the more general (#>)/2:
minimo([X], X) :- !.
minimo([X,Y|Tail], N):-
( X #> Y ->
minimo([Y|Tail], N)
;
minimo([X|Tail], N)
).
?- minimo([a,b,3,2,1],S).
S = 1.
First of all, I don't think the proposed implementation is very elegant: here they pass the minimum found element thus far by constructing a new list each time. Using an additional parameter (we call an accumulator) is usually the way to go (and is probably more efficient as well).
In order to solve the problem, we first have to find an integer. We can do this like:
sint([H|T],R) :-
integer(H),
!,
sint(T,H,R).
sint([_|T],R) :-
sint(T,R).
So here we check if the head H is an integer/1. If that is the case, we call a predicate sint/3 (not to be confused with sint/2). Otherwise we call recursively sint/2 with the tail T of the list.
Now we still need to define sint/3. In case we have reached the end of the list [], we simply return the minum found thus far:
sint([],R,R).
Otherwise there are two cases:
the head H is an integer and smaller than the element found thus far, in that case we perform recursion with the head as new current minimum:
sint([H|T],M,R):
integer(H),
H < M,
!,
sint(T,H,R).
otherwise, we simply ignore the head, and perform recursion with the tail T.
sint([_|T],M,R) :-
sint(T,M,R).
We can put the recursive clauses in an if-then-else structure. Together with the earlier defined predicate, the full program then is:
sint([H|T],R) :-
integer(H),
!,
sint(T,H,R).
sint([_|T],R) :-
sint(T,R).
sint([],R,R).
sint([H|T],M,R):
(
(integer(H),H < M)
-> sint(T,H,R)
; sint(T,M,R)
).
The advantage of this approach is that filtering and comparing (to obtain the minimum) is done at the same time, so we only iterate once over the list. This will usually result in a performance boost since the "control structures" are only executed once: more is done in an iteration, but we only iterate once.
We can generalize the approach by making the filter generic:
filter_minimum(Filter,[H|T],R) :-
Goal =.. [Filter,H],
call(Goal),
!,
filter_minimum(Filter,T,H,R).
filter_minimum(Filter,[_|T],R) :-
filter_minimum(Filter,T,R).
filter_minimum(_,[],R,R).
filter_minimum(Filter,[H|T],M,R) :-
Goal =.. [Filter,H],
(
(call(Goal),H < M)
-> filter_minimum(Filter,T,H,R)
; filter_minimum(Filter,T,M,R)
).
You can then call it with:
filter_minimum(integer,[a,b,3,2,1],R).
to filter with integer/1 and calculate the minimum.
You could just write a predicate that returns a list with the numbers and the use the above minimo/2 predicate:
only_numbers([],[]).
only_numbers([H|T],[H|T1]):-integer(H),only_numbers(T,T1).
only_numbers([H|T],L):- \+integer(H),only_numbers(T,L).
sint(L,S):-only_numbers(L,L1),minimo(L1,S).
I am a newbie to prolog and am trying to write a program which returns the atoms in a well formed propositional formula. For instance the query ats(and(q, imp(or(p, q), neg(p))), As). should return [p,q] for As. Below is my code which returns the formula as As. I dont know what to do to split the single F in ats in the F1 and F2 in wff so wff/2 never gets called. Please I need help to proceed from here. Thanks.
CODE
logical_atom( A ) :-
atom( A ),
atom_codes( A, [AH|_] ),
AH >= 97,
AH =< 122.
wff(A):- ground(A),
logical_atom(A).
wff(neg(A)) :- ground(A),wff(A).
wff(or(F1,F2)) :-
wff(F1),
wff(F2).
wff(and(F1,F2)) :-
wff(F1),
wff(F2).
wff(imp(F1,F2)) :-
wff(F1),
wff(F2).
ats(F, As):- wff(F), setof(F, logical_atom(F), As).
First, consider using a cleaner representation: Currently, you cannot distinguish atoms by a common functor. So, wrap them for example in a(Atom).
Second, use a DCG to describe the relation between a well-formed formula and the list of its atoms, like in:
wff_atoms(a(A)) --> [A].
wff_atoms(neg(F)) --> wff_atoms(F).
wff_atoms(or(F1,F2)) --> wff_atoms(F1), wff_atoms(F2).
wff_atoms(and(F1,F2)) --> wff_atoms(F1), wff_atoms(F2).
wff_atoms(imp(F1,F2)) --> wff_atoms(F1), wff_atoms(F2).
Example query and its result:
?- phrase(wff_atoms(and(a(q), imp(or(a(p), a(q)), neg(a(p))))), As).
As = [q, p, q, p].
This should do what you want. It extracts the unique set of atoms found in any arbitrary prolog term.
I'll leave it up to you, though, to determine what constitutes a "well formed propositional formula", as you put it in your problem statement (You might want to take a look at DCG's for parsing and validation).
The bulk of the work is done by this "worker predicate". It simply extracts, one at a time via backtracking, any atoms found in the parse tree and discards anything else:
expression_atom( [T|_] , T ) :- % Case #1: head of list is an ordinary atom
atom(T) , % - verify that the head of the list is an atom.
T \= [] % - and not an empty list
. %
expression_atom( [T|_] , A ) :- % Case #2: head of listl is a compound term
compound(T) , % - verify that the head of the list is a compound term
T =.. [_|Ts] , % - decompose it, discarding the functor and keeping the arguments
expression_atom(Ts,A) % - recurse down on the term's arguments
. %
expression_atom( [_|Ts] , A ) :- % Finally, on backtracking,
expression_atom(Ts,A) % - we simply discard the head and recurse down on the tail
. %
Then, at the top level, we have this simple predicate that accepts any [compound] prolog term and extracts the unique set of atoms found within by the worker predicate via setof/3:
expression_atoms( T , As ) :- % To get the set of unique atoms in an arbitrary term,
compound(T) , % - ensure that's its a compound term,
T =.. [_|Ts] , % - decompose it, discarding the functor and keeping the arguments
setof(A,expression_atom(Ts,A),As) % - invoke the worker predicate via setof/3
. % Easy!
I'd approach this problem using the "univ" operator =../2 and explicit recursion. Note that this solution will not generate and is not "logically correct" in that it will not process a structure with holes generously, so it will produce different results if conditions are reordered. Please see #mat's comments below.
I'm using cuts instead of if statements for personal aesthetics; you would certainly find better performance with a large explicit conditional tree. I'm not sure you'd want a predicate such as this to generate in the first place.
Univ is handy because it lets you treat Prolog terms similarly to how you would treat a complex s-expression in Lisp: it converts terms to lists of atoms. This lets you traverse Prolog terms as lists, which is handy if you aren't sure exactly what you'll be processing. It saves me from having to look for your boolean operators explicitly.
atoms_of_prop(Prop, Atoms) :-
% discard the head of the term ('and', 'imp', etc.)
Prop =.. [_|PropItems],
collect_atoms(PropItems, AtomsUnsorted),
% sorting makes the list unique in Prolog
sort(AtomsUnsorted, Atoms).
The helper predicate collect_atoms/2 processes lists of terms (univ only dismantles the outermost layer) and is mutually recursive with atoms_of_prop/2 when it finds terms. If it finds atoms, it just adds them to the result.
% base case
collect_atoms([], []).
% handle atoms
collect_atoms([A|Ps], [A|Rest]) :-
% you could replace the next test with logical_atom/1
atom(A), !,
collect_atoms(Ps, Rest).
% handle terms
collect_atoms([P|Ps], Rest) :-
compound(P), !, % compound/1 tests for terms
atoms_of_prop(P, PAtoms),
collect_atoms(Ps, PsAtoms),
append(PAtoms, PsAtoms, Rest).
% ignore everything else
collect_atoms([_|Ps], Rest) :- atoms_of_prop(Ps, Rest).
This works for your example as-is:
?- atoms_of_prop(ats(and(q, imp(or(p, q), neg(p))), As), Atoms).
Atoms = [p, q].
I starting to study for my upcoming exam and I'm stuck on a trivial prolog practice question which is not a good sign lol.
It should be really easy, but for some reason I cant figure it out right now.
The task is to simply count the number of odd numbers in a list of Int in prolog.
I did it easily in haskell, but my prolog is terrible. Could someone show me an easy way to do this, and briefly explain what you did?
So far I have:
odd(X):- 1 is X mod 2.
countOdds([],0).
countOdds(X|Xs],Y):-
?????
Your definition of odd/1 is fine.
The fact for the empty list is also fine.
IN the recursive clause you need to distinguish between odd numbers and even numbers. If the number is odd, the counter should be increased:
countOdds([X|Xs],Y1) :- odd(X), countOdds(Xs,Y), Y1 is Y+1.
If the number is not odd (=even) the counter should not be increased.
countOdds([X|Xs],Y) :- \+ odd(X), countOdds(Xs,Y).
where \+ denotes negation as failure.
Alternatively, you can use ! in the first recursive clause and drop the condition in the second one:
countOdds([X|Xs],Y1) :- odd(X), !, countOdds(Xs,Y), Y1 is Y+1.
countOdds([X|Xs],Y) :- countOdds(Xs,Y).
In Prolog you use recursion to inspect elements of recursive data structs, as lists are.
Pattern matching allows selecting the right rule to apply.
The trivial way to do your task:
You have a list = [X|Xs], for each each element X, if is odd(X) return countOdds(Xs)+1 else return countOdds(Xs).
countOdds([], 0).
countOdds([X|Xs], C) :-
odd(X),
!, % this cut is required, as rightly evidenced by Alexander Serebrenik
countOdds(Xs, Cs),
C is Cs + 1.
countOdds([_|Xs], Cs) :-
countOdds(Xs, Cs).
Note the if, is handled with a different rule with same pattern: when Prolog find a non odd element, it backtracks to the last rule.
ISO Prolog has syntax sugar for If Then Else, with that you can write
countOdds([], 0).
countOdds([X|Xs], C) :-
countOdds(Xs, Cs),
( odd(X)
-> C is Cs + 1
; C is Cs
).
In the first version, the recursive call follows the test odd(X), to avoid an useless visit of list'tail that should be repeated on backtracking.
edit Without the cut, we get multiple execution path, and so possibly incorrect results under 'all solution' predicates (findall, setof, etc...)
This last version put in evidence that the procedure isn't tail recursive. To get a tail recursive procedure add an accumulator:
countOdds(L, C) :- countOdds(L, 0, C).
countOdds([], A, A).
countOdds([X|Xs], A, Cs) :-
( odd(X)
-> A1 is A + 1
; A1 is A
),
countOdds(Xs, A1, Cs).