labeled sets version ok & tested.

evidence.pl

@@ -64,16 +64,24 @@ combine([Mass1|Masses1], Masses2, RMasses, Opts) :-
     append(RMasses1, RMasses2, RMasses).
 
 combine1(_, [], [], _).
-combine1((Set1, Mass1), [(Set2, _)|L], Result, Opts) :-
+combine1((Label1, Set1, Mass1), [(_, Set2, _)|L], Result, Opts) :-
+    % empty intersection case
     ord_intersect(Set1, Set2, []), % empty intersection case
     trace('~w inter ~w = emptyset~n', [Set1, Set2], Opts, 2),
-    combine1((Set1, Mass1), L, Result, Opts).
-combine1((Set1, Mass1), [(Set2, Mass2)|L], [(RSet, RMass)|Result], Opts) :-
+    combine1((Label1, Set1, Mass1), L, Result, Opts).
+combine1((Label1, Set1, Mass1), [(Label2, Set2, Mass2)|L], [(RLabel, RSet, RMass)|Result], Opts) :-
     ord_intersect(Set1, Set2, RSet),
     RSet \= [], % nonempty intersection case
     RMass is Mass1 * Mass2,
+    (   memberchk(0, Label1)
+    ->  RLabel = Label2
+    ;   (   memberchk(0, Label2)
+        ->  RLabel = Label1
+        ;   ord_union(Label1, Label2, RLabel)
+        )
+    ),
     trace('~w inter ~w = ~w : ~w~n', [Set1, Set2, RSet, RMass], Opts, 2),
-    combine1((Set1, Mass1), L, Result, Opts).
+    combine1((Label1, Set1, Mass1), L, Result, Opts).
 
 %!  normalize(+BBA, -NormBBA) is det
 %
@@ -94,22 +102,24 @@ normalize(M1, M2) :-
 %
 %   Merge duplicate sets and add their masses.
 merge_unique([], []).
-merge_unique([(Set, M1)|B1], [(Set, M2)|B3]) :-
-    collect_masses_unique(Set, B1, Masses, B2),
+merge_unique([(Label, Set, M1)|B1], [(Label, Set, M2)|B3]) :-
+    collect_masses_unique((Label, Set), B1, Masses, B2),
     M2 is M1 + Masses,
     merge_unique(B2, B3).
 
-%!  collect_masses_unique(+Set, +BBas, -Masses, -B2) is det
+%!  collect_masses_unique(+LabelSet, +BBas, -Masses, -B2) is det
 %
 %   Masses is the sum of all masses of be belief assignments in BBAs
-%   concerning set Set. B2 containts the remaining assignments.
+%   concerning (Label, Set). B2 containts the remaining
+%   assignments.
 collect_masses_unique(_, [], 0, []).
-collect_masses_unique(Set, [(Set, M1)|BBAs], Masses, FinalBBAs) :-
-    collect_masses_unique(Set, BBAs, M2, FinalBBAs),
+collect_masses_unique((Label, Set), [(Label, Set, M1)|BBAs], Masses, FinalBBAs) :-
+    collect_masses_unique((Label, Set), BBAs, M2, FinalBBAs),
     Masses is M1 + M2.
-collect_masses_unique(Set, [(S1, M1)|BBAs], Masses, [(S1, M1)|FinalBBAs]) :-
-    Set \== S1,
-    collect_masses_unique(Set, BBAs, Masses, FinalBBAs).
+collect_masses_unique((Label, Set), [(Label1, S1, M1)|BBAs], Masses, [(Label1, S1, M1)|FinalBBAs]) :-
+    (   Set \== S1 ; Label \== Label1
+    ),
+    collect_masses_unique((Label, Set), BBAs, Masses, FinalBBAs).
 
 %!  add_all(+L, -Sum) is semidet
 %
@@ -124,7 +134,7 @@ add_all([N|L], S) :-
 %
 %   Sum is the sum of the masses in IMasses BBA
 sum_mass([], 0).
-sum_mass([(_,M)|L], S) :-
+sum_mass([(_, _, M)|L], S) :-
     sum_mass(L, S1),
     S is S1 + M.
 
@@ -132,7 +142,7 @@ sum_mass([(_,M)|L], S) :-
 %
 %   Multiply a BBA L1 by a factor F.
 mult(_, [], []).
-mult(F, [(S1,N1)|L1], [(S1,N2)|L2]) :-
+mult(F, [(Lb1, S1, N1)|L1], [(Lb1, S1, N2)|L2]) :-
     N2 is N1 * F,
     mult(F, L1, L2).
 
@@ -171,27 +181,30 @@ global_bba2(B, [BBa|BBas], GBBA, Opts) :-
 %
 %   Bel is the set of beliefs for each Bi, given the global BBA GBBA.
 beliefs([], _, []).
-beliefs([Bi|Bis], GBBA, [(Bi, Bel)|Bels]) :-
-    belief(Bi, GBBA, Bel),
+beliefs([Ni/Bi|Bis], GBBA, [(Ni, Bi, Bel)|Bels]) :-
+    belief(Ni/Bi, GBBA, Bel),
     beliefs(Bis, GBBA, Bels).
 
 belief(_, [], 0).
-belief(Bi, [(Bj, M)|GBBA], Bel) :-
+belief(Ni/Bi, [(Nj, Bj, M)|GBBA], Bel) :-
     ord_subset(Bj, Bi),
-    belief(Bi, GBBA, Bel1),
+    memberchk(Ni, Nj),
+    belief(Ni/Bi, GBBA, Bel1),
     Bel is M + Bel1.
-belief(Bi, [(Bj, _)|GBBA], Bel) :-
-    \+ ord_subset(Bj, Bi),
-    belief(Bi, GBBA, Bel).
+belief(Ni/Bi, [(Nj, Bj, _)|GBBA], Bel) :-
+    (   \+ ord_subset(Bj, Bi) ; \+ memberchk(Ni, Nj) ),
+    belief(Ni/Bi, GBBA, Bel).
 
-%!  print_beliefs(+Bels) is semidet
+
+%!  print_beliefs(+Bels, +Assoc) is semidet
+%
+%   essentially used for debugging.
 
 print_beliefs([]).
-print_beliefs([(Bi, Bel)|Bels]) :-
-    format('Bel(~w)=~w~n', [Bi, Bel]),
+print_beliefs([(Li, Bi, Bel)|Bels]) :-
+    format('Bel(~w={~w})=~w~n', [Li, Bi, Bel]),
     print_beliefs(Bels).
 
-
 /**********************************************************************/
 /* test data                                                          */
 /**********************************************************************/

wbel.pl

@@ -155,11 +155,12 @@ print_raw_beliefs([(Bi, Bel)|Bels]) :-
 %!  print_beliefs(+Bels, +Assoc) is semidet
 
 print_beliefs([], _).
-print_beliefs([(Bi, Bel)|Bels], Assoc) :-
-    expand_formulae(Bi, Assoc, FBi),
-    format('Bel(~w)=~w~n', [FBi, Bel]),
+print_beliefs([(Li, Bi, Bel)|Bels], Assoc) :-
+    expand_formulae(Bi, Assoc, Forms),
+    format('Bel(~w={~w})=~w~n', [Li, Forms, Bel]),
     print_beliefs(Bels, Assoc).
 
+
 %!  print_wincl(+Bels,+Assoc) is semidet
 %
 %   print sets of formulas.
@@ -201,8 +202,8 @@ generate_b1(N, CountDown, [T|L], Func) :-
 %
 %   collect ASP answer sets
 %   Each answer set represent subbase of B which is maximaly consistent
-%   with mu. Number each base, that is, the results is a list of
-%   i/List terms.
+%   with mu. Number each base (starting from 1), that is, the results is
+%   a list of i/List terms.
 collect_results([], [], _) :- !.
 collect_results([as(L)|L1], [N/SL|L2], N) :-
     !,