关键词: 多智能体系统, 平衡参数自适应, 网络碎片度量, 拓扑优化

Abstract: Making full use of the high-order information in the multi-agent network structure can effectively enforce the multi-agent consensus.The algorithm proposed by motif-aware weighted multi-agent system(MWMS) focuses on the extraction of connection information in the complex network,ignoring the fragment information in the network,resulting in a large difference in the convergence effect of MWMS when taking different balance parameter values.To address the aforementioned issues,this paper proposes an alpha-adaptive motif-aware weighted multi-agent system(AMWMS) to reveal the regulatory patterns of balance parameters for MASs in hybrid-order networks.Firstly,this paper proposes methods for quantifying the degree of high-order network fragmentation based on Jaccard similarity and the degree of low-order network fragmentation based on relative distance,which are used for modeling different layer network fragment information.Secondly,an adaptive parameter generation hybrid-order network(APGHNet) is designed,and its balance parameter can adaptively change during system evolution.Finally,this paper proposes a motif-aware weighted multi-agent consensus protocol with trade-off parameter adaptation.Simulation results show that the balance parameter adaptive method of the new protocol is effective by comparing with the consistency protocol in MWMS,and the system can eventually converge to fewer clusters to enforce the system consensus.

Key words: Multi agent systems, Trade-off parameter adaptation, Network fragmentation quantification, Topology optimization