DocumentCode :
1661881
Title :
Agent-based model toward organizational computing: from organizational learning to genetics-based machine learning
Author :
Takadama, Keiki ; Shimohara, Katsunori ; Terano, Takao
Author_Institution :
ATR Human Inf. Process. Res. Labs., Kyoto, Japan
Volume :
2
fYear :
1999
fDate :
6/21/1905 12:00:00 AM
Firstpage :
604
Abstract :
Explores agent-based approaches toward organizational computing models by using an organizational-learning oriented classifier system (OCS) and investigates problems in the conventional definitions/models of OL. A detailed analysis of the relationship between OCS and conventional definitions/models has revealed that (1) agent-based approaches toward organizational computing models provide detailed understanding of organizations; (2) conventional definitions/models of OL lack the concrete relationship between individual and organization
Keywords :
corporate modelling; learning systems; multi-agent systems; software agents; agent-based model; classifier system; genetics-based machine learning; organizational computing; organizational learning; Analytical models; Computational modeling; Concrete; Cybernetics; Humans; Machine learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on
Conference_Location :
Tokyo
ISSN :
1062-922X
Print_ISBN :
0-7803-5731-0
Type :
conf
DOI :
10.1109/ICSMC.1999.825329
Filename :
825329
Link To Document :
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