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
Link To Document :
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