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
fDate :
6/21/1905 12:00:00 AM
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;
Conference_Titel :
Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on
Conference_Location :
Tokyo
Print_ISBN :
0-7803-5731-0
DOI :
10.1109/ICSMC.1999.825329