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    Time-varying diffusion social learning

    Date
    2020-03-30
    Author
    Rana, Vidhi
    Kwon, Hyuck M.
    Murrell, David A.
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    Citation
    V. Rana, H. M. Kwon and D. A. Murrell, "Time-Varying Diffusion Social Learning," 2020 International Conference on Computing, Networking and Communications (ICNC), Big Island, HI, USA, 2020, pp. 282-286
    Abstract
    This paper studies a time-varying diffusion social learning algorithm, for an agent in a network trying to learn a true hypothesis (or state). We will show that agents in a weakly connected sub-network will be under the influence of agents in the strongly connected sub-network, which leads to a mind control scenario. We will derive analytical expressions of the limiting beliefs of the agents in the time-varying network. Moreover, we will extend the results of time-varying weakly connected networks to the case where agents assign decreasing weights to neighboring agents.
    Description
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    URI
    https://doi.org/10.1109/ICNC47757.2020.9049755
    https://soar.wichita.edu/handle/10057/17530
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