Fig. 2
From: Integrating graph and reinforcement learning for vaccination strategies in complex networks
The degradation of network structures resulting from the removal of 20% nodes by different models on synthetic datasets with various properties. Each dimension has been scaled to fall within a range of 0 to 1 to enhance visualization. To ensure consistency in the result display, we use the inverse of component number and epidemic threshold as the measurement. This means a lower reciprocal value signals a stronger ability of the network to prevent the spread of pathogens. The proposed method proves to be the most effective in dismantling the network structure, leaving the smallest area remaining in each dataset.
