Research on Autonomous Reconstruction Method for Dependent Combat Networks
Yunpeng Sun, Tingting Zhang
Abstract
Cascade effects arising from the interoperability of weapon systems in a dynamic battlefield environment make the combat system-of-systems (CSoS) portfolio decision a problem. In this article, we propose an integrated CSoS autonomous decision-making method framework for solving the autonomous planning problem of CSoS. Specifically, we employ a functional dependency network analysis method to capture the interdependencies between heterogeneous equipment and construct a dependent combat network (DCN). The network structure is considered as a decision action space, the CSoS formation process is considered as a portfolio decision process of the combat network, and then, an approximate dynamic programming method is employed to obtain the optimal policy function for CSoS. Finally, the validity of the proposed method is verified through a DCN case study. The results indicate that the CSoS reconstructed according to the optimal policy function restores an average of 20.2% of the lost operational capability under four attack scenarios. This study provides a technical method for autonomous planning and decision making of CSoS.