Finding key players in complex networks through deep reinforcement learning

Finding an optimal set of nodes, called key players, whose activation (or removal) would maximally enhance (or degrade) a certain network functionality, is a fundamental class of problems in network science. Potential applications include network immunization, epidemic control, drug design and viral...

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Veröffentlicht in:	Nature machine intelligence 2020-06, Vol.2 (6), p.317-324
Hauptverfasser:	Fan, Changjun, Zeng, Li, Sun, Yizhou, Liu, Yang-Yu
Format:	Artikel
Sprache:	eng
Schlagworte:	639/705/117 639/766/530/2801 Algorithms Complexity Connectivity Deep learning Design Engineering Graph representations Immunization Machine learning Networks Players Polynomials Terrorism
Online-Zugang:	Volltext
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