Abstract
Recent results from social science have indicated that neighborhood effects have an important role in an evacuation decision by a family. Neighbors evacuating can motivate a family to evacuate. On the other hand, if a lot of neighbors evacuate, then the likelihood of an individual or family deciding to evacuate decreases, for fear of looting. Such behavior cannot be captured using standard models of contagion spread on networks, e.g., threshold models. Here, we propose a new graph dynamical system model, 2mode-threshold, which captures such behaviors. We study the dynamical properties of 2mode-threshold in different networks, and find significant differences from a standard threshold model. We demonstrate the utility of our model through agent based simulations on small world networks of Virginia Beach, VA. We use it to understand evacuation rates in this region, and to evaluate the effects of the model and of different initial conditions on evacuation decision dynamics.
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Acknowledgment
We thank the anonymous reviewers for their insights. This work has been partially supported by the following grants: NSF CRISP 2.0 Grant 1832587, DTRA CNIMS (Contract HDTRA1-11-D-0016-0001), NSF DIBBS Grant ACI-1443054, NSF EAGER Grant CMMI-1745207, and NSF BIG DATA Grant IIS-1633028.
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Halim, N., Kuhlman, C.J., Marathe, A., Mozumder, P., Vullikanti, A. (2020). Two-Mode Threshold Graph Dynamical Systems for Modeling Evacuation Decision-Making During Disaster Events. In: Cherifi, H., Gaito, S., Mendes, J., Moro, E., Rocha, L. (eds) Complex Networks and Their Applications VIII. COMPLEX NETWORKS 2019. Studies in Computational Intelligence, vol 881. Springer, Cham. https://doi.org/10.1007/978-3-030-36687-2_43
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DOI: https://doi.org/10.1007/978-3-030-36687-2_43
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