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Solution_found  true; goto step 5;
end;
else
goto step 3;
end;
end;
Step 5: if not Solution_found then There is no solution found;
else Solution is a solution of the problem;
Example 3.3: Consider the network (O, F) in example 3.2, and the problem HG, where
H = O 1 .a, O 1 .A, and G = O 2 .a.
Here we have: M(f 1 ) =  O 1 .c , O 3 .a , M(f 2 ) =  O 1 .b , O 4 .a , M(f 3 ) =  O 2 .b , O 4 .a ,
M(f 4 ) =  O 2 .c , O 3 .a , M(f 5 ) =  O 1 . , O 2 . ,
M =  O 1 .a, O 1 .b, O 1 .c, O 1 .A, O 2 .b, O 2 .c, O 2 .A , O 2 .a, O 3 .a, O 4 .a .
The above algorithms will produce the solution D =  f 5 , O 1 , f 1 , f 2 , f 3 , f 4 , O 2 , and the process
of extending the set of attributes as follows:
 A 1
  A 2
 A 4
 A 5
 A 6
  A 7
 A 3
A 0
5
1
2
3
4
2
1
with
A 0 = A = O 1 .a , O 1 .A,
A 1 = O 1 .a , O 1 .A, O 2 .A,
A 2 =  O 1 .a , O 1 .A, O 2 .A, O 1 .b, O 1 .c ,
A 3 = O 1 .a , O 1 .A, O 2 .A, O 1 .b, O 1 .c, O 3 .a,
A 4 = O 1 .a , O 1 .A, O 2 .A, O 1 .b, O 1 .c, O 3 .a, O 4 .a,
A 5 = O 1 .a , O 1 .A, O 2 .A, O 1 .b, O 1 .c, O 3 .a, O 4 .a, O 2 .b,
A 6 = O 1 .a , O 1 .A, O 2 .A, O 1 .b, O 1 .c, O 3 .a, O 4 .a, O 2 .b, O 2 .c,
A 7 = O 1 .a , O 1 .A, O 2 .A, O 1 .b, O 1 .c, O 3 .a, O 4 .a, O 2 .b, O 2 .c, O 2 .a.
3.2.3 Extensions of computational networks
Computational Networks with simple valued variables and networks of computational
objects can be used to represent knowledge in many domains of knowledge. The basic
components of knowledge consist of a set of simple valued variables and a set of
computational relations over the variables. However, there are domains of knowledge based
on a set of elements, in which each element can be a simple valued variables or a function.
For example, in the knowledge of alternating current the alternating current intensity i(t)
and the alternating potential u(t) are functions. It requires considering some extensions of
computational networks such as extensive computational networks and extensive computational
objects networks that are defined below.
Definition 3.9: An extensive computational network is a structure (M,R) consisting of two
following sets:
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