Abstract
Recognizing military coordination relationships among adversarial operations is essential in task planning and decision making. Due to the complexity of modern informationized war, it is challenging to analyze the diverse relations between entities in the war situation. In this study, we propose a novel framework based on knowledge graph to predict operational coordinations. We first construct a novel large scale knowledge graph that consits of 29313 nodes and 191542 edges from Wargame Competition dataset. The embedding method jointly considers information from node attributes, local situations and global structure, and then combine the three parts with a self-attention mechanism. Experiments compared with baselines demonstrate that the proposed model is more accurate and robust than existing methods.
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Song, C. et al. (2022). A Knowledge Graph Based Approach to Operational Coordination Recognition in Wargame. In: Fan, W., Zhang, L., Li, N., Song, X. (eds) Methods and Applications for Modeling and Simulation of Complex Systems. AsiaSim 2022. Communications in Computer and Information Science, vol 1712. Springer, Singapore. https://doi.org/10.1007/978-981-19-9198-1_38
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DOI: https://doi.org/10.1007/978-981-19-9198-1_38
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