Abstract

In this work, a model for evolving networks is presented based on a Brownian particle. Each time, the Brownian particle enters the network through a randomly selected node. The random walk is terminated after having created m-links with visited nodes. Two strategies have been tested: in the first one, we used a generalized algorithm for the secretary problem in order to maximize the degree of the node with which the new node is connected, while in the second strategy, the Brownian particle creates links with nodes that meets twice. In all cases, scale free, modular, dissasortative networks are created.

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