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Afterwards, the constants were 80 again. 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. As a result, one number was sufficient to
describe the state of coefficients vectors at any iteration. In addition, Al averaged across all
modules also was used as a characteristic of the process.
It was suggested that owing to stable processors filled by 80 the coefficient vectors of the
model with stable processors (CV-sp) should exceed those of the model without stable
processors (CV-wsp) at stage 2. Moreover, CV-sp should be more stable after a sudden
fluctuation in the constants of the environment. Also, AL-sp should be more than AL-wsp.
The results of both simulations are in figure 2, where for convenience, ALs were multiplied
by 100.
100
90
80
St
a
ge
1
S
tag
e
2
70
60
50
40
30
Fluct
u
atio
n
20
10
CV-sp
Al-sp
CV-wsp
AL-wsp
0
0123456789 0 1 2 3 4 5 6
Iterations
Fig. 2. The comparison of the results of two simulations.
4.2 A model with perceptive spot (model 2)
Though model 1 is able to demonstrate some characteristics of goal-directed activity, it
seems too primitive for serious actions. Model 2 is more complex, its system has a
perceptive spot, which includes the modules whose input vectors are filled by a useful
signal from the environment while the input vectors of the other modules are filled by noise.
Both a useful signal and noise are real numbers but the amplitude of noise is considerably
less. The system is able to move the center of the spot but cannot change its size. The
