Finding influential agent groups in complex multiagent software systems based on citation network analyses |
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| Affiliation: | 1. Department of Computer Science, City University of Hong Kong, Hong Kong, China;2. School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, China;3. School of Computer and Information Engineering, Shanghai University of Electric Power, Shanghai 200090, China;1. Institute of Physics Belgrade, Pregrevica 118, 11080 Zemun-Belgrade, Serbia;2. IMTEL-Communication, Bulevar Mihajla Pupina 165b, 11070 Belgrade, Serbia;3. Wireless Communications Research Group, University of Westminster, London W1W 6UW, UK;4. School of Electrical Engineering, University of Belgrade, 11120 Belgrade, Serbia;5. ECE Department, Colorado State University, Fort Collins, CO 80523-1373, USA;1. Materials Research Center for Element Strategy, Tokyo Institute of Technology, Mailbox SE-1, 4259 Nagatsuta, Midori-ku, Yokohama 226-8503, Japan;2. Laboratory for Materials and Structures, Institute of Innovative Research, Tokyo Institute of Technology, 4259 Nagatsuta, Midori-ku, Yokohama 226-8503, Japan;3. ACCEL Program, Japan Science and Technology Agency, Kawaguchi 332-0012, Japan;4. New Product R&D Center, Asahi Glass Co. Ltd, 1150 Hazawa, Kanagawa-ku, Yokohama 221-8755, Japan |
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| 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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| Keywords: | Complex software systems Multiagent software systems Agent groups Citation networks Group centrality Group influence |
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