Zhi-Xi Wu
Lanzhou University
132 Papers
360 Citations
Zhi-Xi Wu is an academic researcher from Lanzhou University. The author has contributed to research in topics: Population & Prisoner's dilemma. The author has an hindex of 35, co-authored 120 publications. Previous affiliations of Zhi-Xi Wu include University of Hong Kong & City University of Hong Kong.
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Papers
Diversity-optimized cooperation on complex networks.
TL;DR: It is found that there exists an optimal value of alpha, for which the level of cooperation reaches maximum, and the results suggest that in order to achieve strong cooperation on a complex network, individuals should learn more frequently from neighbors with higher degrees, but only to a certain extent.
Modeling scientific-citation patterns and other triangle-rich acyclic networks.
TL;DR: The optimal parameter values suggest that the impact of scientific papers, at least in the empirical data set the authors model, is proportional to the inverse of the number of papers since they were published.
Abrupt transition to complete congestion on complex networks and control.
TL;DR: A mean-field theory is developed to explain the surprising transition phenomenon and a control strategy based on the idea of random packet dropping to prevent/break complete congestion is proposed.
Kinetic-exchange-like opinion dynamics in complex networks: roles of the dimensionality and local interaction topology
TL;DR: In this paper, a kinetic exchange-like opinion dynamics model with both positive and negative interactions in various complex networks is studied, where the control parameter p ∈ [0, 1] denotes the probability of the presence of negative outcome in the pairwise interaction and the average opinion of the population serves as the order parameter of the system.
Robustness and Vulnerability of Networks with Dynamical Dependency Groups
TL;DR: This study theoretically finds that an abrupt percolation transition exists corresponding to the dynamical dependency groups for a wide range of topologies after initial random removal and proposes an analytical framework for random networks with arbitrary degree distribution.