Finding influential agent groups in complex multiagent software systems based on citation network analyses

Abstract Current complex engineering software systems are often composed of many components and can be built based on a multiagent approach, resulting in what are called complex multiagent software systems. In a complex multiagent software system, various software agents may cite the operation results of others, and the citation relationships among agents form a citation network; therefore, the importance of a software agent in a system can be described by the citations from other software agents. Moreover, the software agents in a system are often divided into various groups, and each group contains the agents undergoing similar tasks or having related functions; thus, it is necessary to find the influential agent group (not only the influential individual agent) that can influence the system outcome utilities more than the others. To solve such a problem, this paper presents a new model for finding influential agent groups based on group centrality analyses in citation networks. In the presented model, a concept of extended group centrality is presented to evaluate the impact of an agent group, which is collectively determined by both direct and indirect citations from other agents outside the group. Moreover, the presented model addresses two typical types of agent groups: one is the adjacent group where agents of a group are adjacent in the citation network, and the other is the scattering group where agents of a group are distributed separately in the citation network. Finally, we present case studies and simulation experiments to prove the effectiveness of the presented model.

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