Time-varying diffusion social learning
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
Click on the DOI link to access the article (may not be free).