Reinforcement Learning-Based Network Dismantling by Targeting Maximum-Degree Nodes in the Giant Connected Component

Reinforcement Learning-Based Network Dismantling by Targeting Maximum-Degree Nodes in the Giant Connected Component

Tackling the intricacies of network dismantling in complex systems poses significant challenges. This task has relevance across various practical domains, yet traditional approaches focus primarily on singular metrics, such as the number of nodes in the Giant Connected Component (GCC) or the average...

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Bibliographic Details
Main Authors: Shixuan Liu, Tianle Pu, Li Zeng, Yunfei Wang, Haoxiang Cheng, Zhong Liu
Format: Article
Language:English
Published: MDPI AG 2024-09-01
Series:Mathematics
Subjects:
complex networks
network dismantling
graph representation learning
reinforcement learning
Online Access:https://www.mdpi.com/2227-7390/12/17/2766

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https://www.mdpi.com/2227-7390/12/17/2766

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