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accordance with this opinion, the dual-processes models (Stanovich & West, 2000; Evans,
2003) have supposed that the mind includes two components. One component uses
searching procedures and accordingly is responsible for deliberate actions. The other
component, which complies with the systems of the first class, underlies routine, automatic
actions. It is suggested that in routine everyday situations, in which, according to such
theories, the vast majority of actions is performed, the routine component effectively selects
an appropriate action. Searching and planning are involved only in unusual situations.
Some unspecified mechanisms constrain searching in those rare cases when the latter is
necessary.
In my opinion, however, nonroutine and routine situations are intertwined more strongly
than it may be consciously acknowledged. The mind cannot be separated into the two
components. For example, if an individual is hungry, she may open her home refrigerator
without the clear awareness of this process. However, people usually do not open
somebody's refrigerators automatically even if they are hungry. No special intention to
inhibit the wish “to open somebody's refrigerator” is necessary in such situations.
Obviously, there is no universal routine “not to open somebody's refrigerator”, simply
because it is very difficult to define unequivocally and finally what refrigerators are
permitted to open. Therefore, it is necessary to suggest that ongoing goals somehow control
activity when an individual attends to the refrigerator, allowing or forbidding the opening
of the latter. In the same manner, ongoing goals unconsciously involve in most of routine
situations even when the individual believes that some component of her activity is
automatic. With the involvement of ongoing goals in most of everyday situations, the
problem of combinatorial explosion becomes unresolved for the dual-processes models.
Whereas, AI research is not intended directly to imitate human intelligence but it seems
obvious that a certain view on human intelligence is a very important tacit heuristic to AI
researchers and strongly influences AI studies. In my opinion, the analysis of the two
conventional classes of goal-directed systems demonstrates that human activity hardly can
be derived from these classes and this may be a very serious factor constraining AI research.
I suggest that the standard view on possible classes of goal-directed systems is incomplete
and consider a more complex categorization below. I present, based on this classification, a
new view on human goal-directed activity as a characteristic of a particular class of goal-
directed systems. Some ideas on how this class can be represented in the brain are
considered. These ideas form the basis for the simulation of simple models of goal-directed
activity. Some proposals on how this novel understanding of humans as goal-directed
systems can be used to create intelligent systems are also considered in the article.
2. Two-dimensional classification of goal-directed systems and the idea of
joint synthesis
The two classes of goal-directed systems are usually considered as two poles of one axis and
as a result, it seems that there are no other classes. However, a more profound view on the
classes demonstrates that the situation may be more complex. Indeed, the first class contains
goal-directed systems in which basic goals and means are constructed innately and together.
In the systems of the second-class goals and means can be constructed arbitrarily and
separately from each other. It is easy to discern that the words “innately” and “separately”
