DocumentCode
345647
Title
Evolution, emergence, semiosis: components of the model for intelligent system
Author
Meystel, A.
Author_Institution
Drexel Univ., Philadelphia, PA, USA
fYear
1999
fDate
1999
Firstpage
452
Lastpage
454
Abstract
The discussion of intelligent system usually starts with issues of defining intelligence as a set of skills, but always ends with specifying the mechanisms of learning. It is important to address the issue of differences and similarities between the techniques of computational/control learning processes (very similar to the processes of semiosis) and biological learning including evolution of species where the resemblance with semiosis is less obvious. We would like to attract attention to the theory of multilevel processes of evolution which are interpreted in this paper as multiresolutional processes of evolution. Novel explanations are preposed for numerous paradoxes known in the area of computational and biological learning including evolution of species. The direct linkage is demonstrated of learning processes and the development of decision-making mechanisms for single and multiple agents
Keywords
evolution (biological); learning (artificial intelligence); learning systems; biological learning; computational learning; control learning; emergence; intelligent system; learning; multilevel evolution processes; multiresolutional evolution processes; semiosis; Actuators; Biological control systems; Biological system modeling; Biology computing; Computational intelligence; Control systems; Decision making; Evolution (biology); Hardware; Intelligent systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control/Intelligent Systems and Semiotics, 1999. Proceedings of the 1999 IEEE International Symposium on
Conference_Location
Cambridge, MA
ISSN
2158-9860
Print_ISBN
0-7803-5665-9
Type
conf
DOI
10.1109/ISIC.1999.796697
Filename
796697
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