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First, consider the simulation of a goal-directed process with a simple goal. At stage 1, the
constants of the environment were 80, 50, and 20. The center of perceptive spot was
established at 0,85, the size of perceptive spot (p11) was 0,2. In addition, at this stage, p2 was
0,2 and p3 was 4,2. This stage lasted until the mean AL exceeded 0,2. At stage 2 all constants
were 50 and the center of the spot was at 0,5 while p2 and p11 were 0,95 and p3 became 3 at
this and last stages. At the start of the last stage all constants were 30, and the center was
established at 0,25 while p2 and p11 were 0,2 again.
It was suggested that at stage 3 the process was to move perceptive spot to the right where
there were stable processors, thus increasing CP. The state of the vectors of coefficients in
the modules within the spot should meet the relationship between the components of
coefficient vectors of stable processors caused by the different constants of the environment
at stage 1. The components of input and coefficients vectors averaged across the modules
within perceptive spot were used to describe the state of the process along with AL
averaged across all modules. The results are in table 2
The table shows that at stage 3, the process was increasing CP and the relationship between
the components of the vectors of coefficients gradually became similar to that between
constants at stage 1. The opposite relationship between the components of input vectors
results from formula 7, after inserting a constant as an input vector in it and taking the
relationship between the components of CVs into account. Because the constants of the
environment were equal at stage 3, the coefficient vectors of the system were influenced by
these constants and, as a result, the relationship formed at stage 1 tended to disappear. This
corresponds to the completion of the process owing to the influence of the situation. It is
important to note that the action of the system cannot be explained by combination of the
perseveratory activity of trained modules and the inactivity of untrained ones. The fact that
at stage 3 the relationship between the components of the vectors of coefficients was already
weakly present at 0,48, considerably beyond the area of modules changed at stage 1 means
that a process including most modules indeed was formed at stage 2, while increasing the
mean AL at stage 3 implies activity in modules untrained at stage 1.
In another simulation, a process with a complex goal, including two constituents, was
formed. In this simulation, stage 1 was divided in two phases. At the first phase, all
constants were 20, the center of perceptive spot was at 0, 85, p3 was 4,2 while p2 and p11
were 0,2. After eight iterations this phase was completed, all constants became 80 and the
center of perceptive spot was moved to 0,65 without changing p2, p3, and p11. This was the
second phase of stage 1 and four iterations were performed. Stage 2 in this simulation was
the same as in the previous one. At the beginning of the last stage all constants were 10, and
the center was established at 0, 25 while p2 and p11 were 0, 2 again.
It was suggested that the process was to move the center of spot to the right and because
there could be two groups of stable processors. The components of the vectors of coefficients
within the spot could firstly increase and later decrease but the components of input vectors
might change in the opposite direction following formula 7. To some extent, this can be
considered as a very primitive form of multilevel activity.
Because at any moment all constants were identical, the components of input and
coefficients vectors in modules could be averaged within each vector and across all modules
in the spot. As a result, one number was sufficient to describe the state of input or
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