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We study the asymptotic properties of distributed consensus algorithms over switching directed random networks. More specifically, we focus on consensus algorithms over independent and identically distributed, directed random graphs, where each agent can communicate with any other agent with some exogenously specified probability. While different aspects of consensus algorithms over random switching...
In this paper, we study a model of social learning where individuals are under influence of others in their social clique. In our model, each agent receives private noisy signals about an unobservable, underlying state of the world. At the end of each time period, the belief of an individual is equal to the convex combination of her posterior beliefs derived from the signal observed, and the priors...
In this paper, we study the dynamics of a viral spreading process in random geometric graphs (RGG). The spreading of the viral process we consider in this paper is closely related with the eigenvalues of the adjacency matrix of the graph. We deduce new explicit expressions for all the moments of the eigenvalue distribution of the adjacency matrix as a function of the spatial density of nodes and the...
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