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people sometimes are unable to solve simple problems, though their knowledge and skills
are sufficient to find the right solution. To avoid similar difficulties an AI system may use
the goals and means constructed jointly as a seed point in some cases and afterwards
searches for goals and methods that are more suitable.
6. Conclusion
Since the advent of first computers, the idea of construction of artificial intelligence similar to
that of human beings has driven the work of thousands of brilliant scientists and engineers.
However, the result of their activity seems unsatisfactory as compared to, for example,
advances in computer hardware. One of the most fundamental reasons for this situation may
be that the mechanisms of human intelligence are unclear. Though the imitation of human
intelligence is not a necessary characteristic of artificial intelligence, obviously a particular
view on human intelligence is a very important heuristic. Therefore, an incorrect
understanding of human intelligence can be a serious obstacle to construct intelligent systems.
Intelligence is a characteristic of goal-directed systems and two classes of such systems can be
easily derived from observations of animals and human beings. In my opinion, the classes that
underlie most approaches to the construction of artificial intelligence are not sufficient to
explain human activity. A broader classification of goal-directed activities suggests such
processes can be described as a two-dimensional structure rather than a one-dimension one. In
such structure there is a cell where in my opinion, humans can be located i.e., humans are
goal-directed systems that synthesize arbitrary goals and means together. Though the idea of
joint synthesis seems contradictory to some aspects of everyday experience, it is consistent
with psychological evidence. In addition, there is neural evidence favoring this supposition.
Simple computer models demonstrate that the idea of joint synthesis can be applied to
simulate goal-directed activity. I suggest that the idea of joint synthesis can be a useful method
to advance research in the construction of intelligent systems.
7. Appendix
Model 1
p2=3*10 -6 ; p3=0,99; p4=0,001
Model 2
p1=1; p4=2; p5=0, 3; p6=0,98; p7=0,5; p8=0,3; p9=0,8; p10=0,8
8. References
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Bäck, T. (1996). Evolutionary Algorithms in Theory and Practice: Evolution Strategies,
Evolutionary Programming, Genetic Algorithms. Oxford Univ. Press.
Bertalanffy, L. von, (1968). General Systems Theory .
Bertino, E, Piero, G & Zarria, B.C. (2001 ). Intelligent Database Systems . Addison-Wesley
Professional.
Buller, D. J. (1998) DeFreuding evolutionary psychology: adaptation and human motivation,
in Hardcastle, V. G., Ed. Psychology Meets Biology: Connections, Conjectures,
Constraints. MIT Press/Bradford Books. http://cogprints.soton.ac.uk/documents
/disk0/00/00/03/26/cog00000326-00/defreud.htm
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