Gomes, P. F.Fernandes, H. A.Costa, A. A.
11页查看更多>>摘要：In this work, we study the topological transition on the associated networks in a model proposed by Saeedian et al. (Scientific Reports 2019 9:9726), which considers a coupled dynamics of node and link states. Our goal was to better understand the two observed phases, so we use another network structure (the so called random geometric graph - RGG) together with other metrics borrowed from network science. We observed a topological transition on the two associated networks, which are subgraphs of the full network. As the links have two possible states (friendly and non-friendly), we defined each associated network as composed of only one type of link. The (non) friendly associated network has (non) friendly links only. This topological transition was observed from the domain distribution of each associated network between the two phases of the system (absorbing and active). We also showed that another metric from network science called modularity (or assortative coefficient) can also be used as order parameter, giving the same phase diagram as the original order parameter from the seminal work. On the absorbing phase the absolute value of the modularity for each associated network reaches a maximum value, while on the active phase they fall to the minimum value. (C) 2022 Elsevier B.V. All rights reserved.
原文链接:
NSTL
Elsevier
Kim, Jeong-YooLee, Kyu-MinPark, Sung-Hoon
15页查看更多>>摘要：This paper develops an evolutionary approach to investigate whether revealing one's own emotions such as selfishness, altruism or envy has evolved in humans through a process of natural selection. This paper finds two results. First, if the revealing trait (revealing or hiding) and the other-regarding trait (selfish or altruistic/envious) are independent so the four types evolve in a correlated way, both of revealing types and hiding types can survive in the long run. For most parameter values, however, revealing altruism fares better than hiding altruism if individuals' interactions are strategic complements, whereas hiding envy fares better than revealing envy if individuals' interactions are strategic substitutes. Second, for most parameter values, only the revealing types survive if the revealing trait and the other-regarding trait are linked so that the four types evolve independently. (C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Griffin, ChristopherSemonsen, JustinBelmonte, Andrew
19页查看更多>>摘要：We study the network replicator equation and characterize its fixed points on arbitrary graph structures for 2 x 2 symmetric games. We show a relationship between the asymptotic behavior of the network replicator and the existence of an independent vertex set in the graph and also show that complex behavior cannot emerge in 2 x 2 games. This links a property of the dynamical system with a combinatorial graph property. We contrast this by showing that ordinary rock-paper-scissors (RPS) exhibits chaos on the 3-cycle and that on general graphs with >= 3 vertices the network replicator with RPS is a generalized Hamiltonian system. This stands in stark contrast to the established fact that RPS does not exhibit chaos in the standard replicator dynamics or the bimatrix replicator dynamics, which is equivalent to the network replicator on a graph with one edge and two vertices (K2).
原文链接:- NSTL
- Elsevier
Li, Ming-GenFan, Li-MingBao, Jing-Dong
9页查看更多>>摘要：Particle motion often exhibits anomalous diffusion arising from spatial inhomogeneity in the complex structures of soft materials. Spatial inhomogeneity induces a power-law frictional landscape for the mean-squared displacement of particles in a force-free environment; expressly, < x(2)(t)> similar to t(alpha) (i.e., 0 < alpha <= 2). We calculate analytically and numerically this mean-squared displacement. By comparing with a XY system in a logarithmic potential, for which anomalous diffusion transitions occur in regimes from normal diffusion to confinement, we investigated the diffusive dynamics of a realistic system away from its equilibrium state. Spatial nonlocal processes were found to be equivalent to time nonlocal ones (i.e., non-Ohmic memory); specifically, the weaker the effective friction produced, the stronger is the diffusion induced. This overcomes the difficulty encountered when evaluating memory effects in experiments. Aided by the generalized Green-Kubo formula, our model is also compared with diffusion processes obeying the scaling behavior of the velocity correlation function. The present study on anomalous diffusion in inhomogeneous environments is helpful because the phenomenon appears in soft, solid and biological matter. (C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Batac, Rene C.Cirunay, Michelle T.
8页查看更多>>摘要：Studies on road networks, especially on highly-urban areas, have to account not only for the topological (i.e. network structure) but, more so, for the actual physical and geographical constraints that affect the efficiency of transport within the system. Here, we investigate the set of shortest paths across low-betweenness centrality nodes, which are found at the periphery of the network. Travel from one peripheral node to another is characterized by highly sinuous paths, which is expected due to the fact that these nodes represent the most highly inaccessible points in the network. Interestingly, short is not simple, i.e. the shorter paths are more likely to have a broad range of sinuosity values, while longer paths are generally more straight. We propose a categorization of the inaccessibility of peripheral nodes based on topological (network centrality) and spatial (physical dimensions) properties, to determine the most highly-inaccessible locations of the network. Unlike other networked architectures where the nodes and edges can be easily replaced or removed, it is impractical, if not impossible, to flatten down cities to give way for new roads. Studies such as this one can give useful insights for management and improvement of city transportation networks given the current conditions. (C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Clements, Alastair J.Fadai, Nabil T.
17页查看更多>>摘要：Riots originating during, or in the aftermath of, sports events can incur significant costs in damages, as well as large-scale panic and injuries. A mathematical description of sports riots is therefore sought to better understand their propagation and limit these physical and financial damages. In this work, we present an agent-based modelling (ABM) framework that describes the qualitative features of populations engaging in riotous behaviour. Agents, pertaining to either a 'rioter' or a 'bystander' sub-population, move on an underlying lattice and can either be recruited or defect from their re-spective sub-population. In particular, we allow these individual-level recruitment and defection processes to vary with local population density. This agent-based modelling framework provides the unifying link between multi-population stochastic models and density-dependent reaction processes. Furthermore, the continuum description of this ABM framework is shown to be a system of nonlinear reaction-diffusion equations and faithfully agrees with the average ABM behaviour from individual simulations. Finally, we determine the unique correspondence between the underlying individual-level recruitment and defection mechanisms with their population-level counterparts, providing a link between local-scale effects and macroscale rioting phenomena.(C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Pi, BinLi, YuhanFeng, Minyu
12页查看更多>>摘要：Network evolutionary game theory provides a new perspective on how cooperative behaviors emerge in the real world and has been widely investigated. However, most studies assume that players are profiteers and ignore the existence of conformists and that players have memories, which are crucial when people make decisions. In this study, we study a memory-based snowdrift game occurring on networks and propose two strategy-updating rules based on profiteers and conformists while considering the historical strategy, memory strength, payoff information and memory length to discuss the emergence and maintenance of cooperation behaviors. In contrast to previous studies, we introduce the player's degree of cooperation to continuousize player payoffs and we consider it when defining the player's strategy-updating rules. In simulations, we show the evolution of the frequency of cooperation as time progresses and investigate the effects of the payoff parameter, memory strength, memory length and conformist ratio on the frequency of cooperation, and further validate the robustness of our model using different network sizes. Our results show that the memory strength, memory length, and conformist ratio can facilitate the cooperation level of the network over a large parameter area, and that the size of the network has almost no effect on the model, which shows the robustness of our model. Our work may elucidate the study of evolutionary games with conformists and memory effects. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Sun, ZejunSun, YananChang, XinfengWang, Feifei...
20页查看更多>>摘要：The identification of community structures plays a crucial role in analyzing network topology, exploring network functions, and mining potential patterns in complex networks. Many algorithms have been proposed for identifying community structures in static networks from different perspectives. However, most networks in the real world are not static and their structures constantly evolve over time. Identifying community structures in dynamic networks remains a challenging task because of the variability, complexity, and large scale of dynamic networks. In this study, we propose a framework and Matthew effect model for community detection in dynamic networks. Based on this architecture and model, we design a dynamic community detection algorithm called, Dynamic Community Detection based on the Matthew effect (DCDME), which employs a batch processing method to reveal communities incrementally in each network snapshot. DCDME has several desirable benefits: high-quality community detection, parameter-free operation, and good scalability. Extensive experiments on synthetic and real-world dynamic networks have demonstrated that DCDME has many advantages and outperforms several state-of-the-art algorithms.
原文链接:- NSTL
- Elsevier
