This paper proposes a knowledge intensive learning model in a multiagent system, based on the concepts described in organizational learning of management science literature. We examine the validity and feasibility of the model in order to apply it to distributed heterogeneous knowledge systems. We have implemented two typical variations of the model: the Specialists-Model and the Generalists- Model. Using the two variations, we carry out simulation studies on the dynamic behaviors of decision making and learning in the organization of agents. The experiments showed that the model had unique adaptability to the change of environments, by enabling agents to efficiently supplement knowledge each other.(pp. 239-247)
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