Understanding the complexity of the Lévy-walk nature of human mobility with a multi-scale cost/benefit model

ABSTRACTIn quantitative studies on animal movements and foraging, there has been ongoing debate over the relevance of Lévy walk and related stochastic models to understanding mobility patterns of diverse organisms. In this study, we collected and analyzed a large number of GPS logs that tracked the movements of different livestock species in northwestern Kenya. Statistically principled analysis has only found limited evidence for the scale-free movement patterns of the Lévy walk and its variants, even though most of the tracked movements clearly show super-diffusive behavior within the relevant temporal duration. Instead, the analysis has given strong support to composite exponential distributions (composite Brownian walks) as the best description of livestock movement trajectories in a wide array of parameter settings. Furthermore, this support has become overwhelming and near universal under an alternative criterion for model selection. These results illuminate the multi-scale and multi-modal nature of livestock spatial behavior. They also have broader theoretical and empirical implications for the related literature.

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On the Levy-Walk Nature of Human Mobility

IEEE INFOCOM 2008 - The 27th Conference on Computer Communications ◽

10.1109/infocom.2008.145 ◽

2008 ◽

Cited By ~ 213

Author(s):

I. Rhee ◽

M. Shin ◽

S. Hong ◽

K. Lee ◽

S. Chong

Keyword(s):

Human Mobility ◽

Lévy Walk ◽

Levy Walk

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Diffusion

10.1093/oso/9780198753919.003.0014 ◽

2018 ◽

Author(s):

Ginestra Bianconi

Keyword(s):

Random Walks ◽

Spectral Properties ◽

Diffusion Constant ◽

Network Structures ◽

Multilayer Networks ◽

Multilayer Network ◽

Lévy Walk ◽

Number Of Layers ◽

Levy Walk ◽

Speed Up

This chapter addresses diffusion, random walks and congestion in multilayer networks. Here it is revealed that diffusion on a multilayer network can be significantly speed up with respect to diffusion taking place on its single layers taken in isolation, and that sometimes it is possible also to observe super-diffusion. Diffusion is here characterized on multilayer network structures by studying the spectral properties of the supra-Laplacian and the dependence on the diffusion constant among different layers. Random walks and its variations including the Lévy Walk are shown to reflect the improved navigability of multilayer networks with more layers. These results are here compared with the results of traffic on multilayer networks that, on the contrary, point out that increasing the number of layers could be detrimental and could lead to congestion.

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Amoebic Foraging Model of Metastatic Cancer Cells

Symmetry ◽

10.3390/sym13071140 ◽

2021 ◽

Vol 13 (7) ◽

pp. 1140

Author(s):

Daiki Andoh ◽

Yukio-Pegio Gunji

Keyword(s):

Bayesian Inference ◽

Cancer Cells ◽

Metastatic Cancer ◽

Gait Patterns ◽

Lévy Walk ◽

Levy Walk ◽

Unicellular Organisms ◽

Living Organisms ◽

Walk Algorithm ◽

Metastatic Cancer Cells

The Lévy walk is a pattern that is often seen in the movement of living organisms; it has both ballistic and random features and is a behavior that has been recognized in various animals and unicellular organisms, such as amoebae, in recent years. We proposed an amoeba locomotion model that implements Bayesian and inverse Bayesian inference as a Lévy walk algorithm that balances exploration and exploitation, and through a comparison with general random walks, we confirmed its effectiveness. While Bayesian inference is expressed only by P(h) = P(h|d), we introduce inverse Bayesian inference expressed as P(d|h) = P(d) in a symmetry fashion. That symmetry contributes to balancing contracting and expanding the probability space. Additionally, the conditions of various environments were set, and experimental results were obtained that corresponded to changes in gait patterns with respect to changes in the conditions of actual metastatic cancer cells.

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