Self Organization Map for Clustering and Classification in the Ecology of Agent Organizations

来源期刊：中南大学学报(英文版)2000年第1期

论文作者：Dimuthu Chandana Kelegama LIU Li-hua LIU Jian-qin

文章页码：53 - 56

Key words：clustering; classification; agent organizations; agent societies; self-organizing; distributed computing

Abstract: Development of computational agent organizations or“societies”has become the domiant computing paradigm in the arena of Distributed Artificial Intelligence, and many foreseeable future applications need agent organizations, in which diversified agents cooperate in a distributed manner, forming teams. In such scenarios, the agentswould need to know each other in order to facilitate the interactions. Moreover, agents in such an environment are not statically defined in advance but they can adaptively enter and leave an organization. This begs the question of how agents locate each other in orderto cooperate in achieving organizational goals. Locating agents is a quite challengingtask, especially in organizations that involve a large number of agents andwhere the resource avaiability is intermittent. The authors explore here an approach based on self-organization map (SOM) which will serve as a clustering method in the light of the knowledge gathered about various agents. The approach begins by categorizing agents using a selected set of agent properties. These categories are used to derive various ranks and a distance matrix. The SOM algorithm uses this matrix as input to obtain clusters of agents. These clusters reduce the search space, resulting in a relatively short agent search time.