No abstract

This paper is concerned with the problem of multi-UAV roundup inspired by hierarchical cognition consistency learning based on an interaction mechanism. First, a dynamic communication model is constructed to address the interactions among multiple agents. This model includes a simplification of the communication graph relationships and a quantification of information efficiency. Then, a hierarchical cognition consistency learning method is proposed to improve the efficiency and success rate of roundup. At the same time, an opponent graph reasoning network is proposed to address the prediction of targets. Compared with existing multi-agent reinforcement learning (MARL) methods, the method developed in this paper possesses the distinctive feature that target assignment and target prediction are carried out simultaneously. Finally, to verify the effectiveness of the proposed method, we present extensive experiments conducted in the scenario of multi-target roundup. The experimental results show that the proposed architecture outperforms the conventional approach with respect to the roundup success rate and verify the validity of the proposed model.

The robustness of coupled network under cascading failure has attracted a lot of attention. In real word, the networks don’t exist in isolation, and the interdependent network is an important network model. In the process of fault propagation, there is usually delay, and a node may have multiple interdependent links. A cascading failure model based on coupled map latices for small word interdependent network is built in this paper. The research shows that when the external perturbation 3.7<R<4.0, the cascading failure ranges of high-degree and random strategy in interdependent network are close, and the different time-delay can induce different range of cascading failure in interdependent network. The thresholds of the external perturbation are common under different time-delay when the whole interdependent network is failed. The time-delay also can prolong the failure spreading time during which measures can be taken to suppress cascading failures. The research can provide a reference for building high-robust transport interdependent network.