摘要：As an important field of Distributed artificial intelligence (DAI); multi-agent systems (MASs) have attracted the attention of extensive research scholars. Consensus as the most important issue in MAS; much progress has been made in studying the consensus control of MAS; but there are some problems remained largely unaddressed which cause the MAS to lose some useful network structure information. First; multi-agent consensus protocol usually proceeds over the low-order structure by only considering the direct edges between agents; but ignores the higher-order structure of the whole topology network. Second; the existing work assumes all the edges in a topology network have the same weight without exploring the potential diversity of the connections. In this way; multi-agent systems fail to enforce consensus; resulting in fragmentation into multiple clusters. To address the above issues; this paper proposes a Motif-aware Weighted Multi-agent System (MWMS) method for consensus control. We focus more on triangle motif in the network; but it can be extended to other kinds of motifs as well. First; a novel weighted network is used which is the combination of the edge-based lower-order structure and the motif-based higher-order structure; i.e.; hybrid-order structure. Subsequently; by simultaneously considering the quantity and the quality of the connections in the network; a novel consensus framework for MAS is designed to update agents. Then; two baseline consensus algorithms are used in MWMS. In our experiments; we use ten topologies of different shapes; densities and ranges to comprehensively analyze the performance of our proposed algorithms. The simulation results show that the hybrid higher-order network can effectively enhance the consensus of the multi-agent system in different network topologies.
