Show simple item record

dc.contributor.authorRana, Vidhi
dc.contributor.authorKwon, Hyuck M.
dc.contributor.authorMurrell, David A.
dc.identifier.citationV. 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. 282-286en_US
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractThis 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.en_US
dc.relation.ispartofseriesInternational Conference on Computing, Networking and Communications (ICNC);2020
dc.subjectLearning algorithmsen_US
dc.titleTime-varying diffusion social learningen_US
dc.typeConference paperen_US
dc.rights.holder© 2020 IEEEen_US

Files in this item


There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record