Core Middle Layer: GNN Relational Reasoning & DRL Policy Agent (The Filling)
GAT + DQN
Models channel correlations with Graph Attention Networks (GAT), builds dynamic Markov transition graph embeddings, and selects optimal receiver tuning 1 hop ahead of the enemy emitter.
GAT Multi-Head Attention
DQN Actor-Critic
>94.8% Hop Prediction