Fig. 6
From: Integrating graph and reinforcement learning for vaccination strategies in complex networks
The cumulative infection scale on five synthetic networks with 20% of nodes removed by various models, where \(\beta\) = 0.1, \(\gamma\) = 0.01 and \(\rho\) = 0.1. Each network consists of 500 nodes. The proposed approach outperforms the baseline methods across all datasets. For instance, in the scale-free network, immunizing 20% of the nodes identified by the proposed method results in a decrease of the final infection scale from 95.3% to 69.1%, compared to using the GND method. These results represent the average of 100 independent runs.
