Strategic Counterfactual Modeling of Deep-Target Airstrike Systems via Intervention-Aware Spatio-Causal Graph Networks
It addresses the problem of improving AI decision-support for high-level policy modeling in domains like nuclear deterrence simulation, though it appears incremental as it builds on existing graph neural network methods.
This study tackled the lack of structured causal modeling between tactical strike behavior and strategic delay in strategic-level simulations by proposing the Intervention-Aware Spatio-Temporal Graph Neural Network (IA-STGNN), which achieved a 12.8% reduction in MAE and 18.4% increase in Top-5% accuracy compared to baselines.
This study addresses the lack of structured causal modeling between tactical strike behavior and strategic delay in current strategic-level simulations, particularly the structural bottlenecks in capturing intermediate variables within the "resilience - nodal suppression - negotiation window" chain. We propose the Intervention-Aware Spatio-Temporal Graph Neural Network (IA-STGNN), a novel framework that closes the causal loop from tactical input to strategic delay output. The model integrates graph attention mechanisms, counterfactual simulation units, and spatial intervention node reconstruction to enable dynamic simulations of strike configurations and synchronization strategies. Training data are generated from a multi-physics simulation platform (GEANT4 + COMSOL) under NIST SP 800-160 standards, ensuring structural traceability and policy-level validation. Experimental results demonstrate that IA-STGNN significantly outperforms baseline models (ST-GNN, GCN-LSTM, XGBoost), achieving a 12.8 percent reduction in MAE and 18.4 percent increase in Top-5 percent accuracy, while improving causal path consistency and intervention stability. IA-STGNN enables interpretable prediction of strategic delay and supports applications such as nuclear deterrence simulation, diplomatic window assessment, and multi-strategy optimization, providing a structured and transparent AI decision-support mechanism for high-level policy modeling.