Abstract
We study the problem of exploring unknown paths in networks through multiple random walks. It is assumed that a path is explored if it has been passed through by a random walker from the initial node to the terminal node continuously. We derive probability θ ′(t) that a given path in a network is explored by one or more random walkers in t steps on condition that there are many random walkers traveling on the network. Results show that more random walkers are better for exploring the path. The larger length l of the path is, the smaller θ ′(t) is. To explore paths with the same length in three kinds of networks, random walkers need least effort in SWW networks, most effort in BA networks and moderate effort in ER networks.
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Pu, C., Yang, J., Miao, R., Pei, W. (2013). Exploring Unknown Paths in Networks Based on Multiple Random Walks. In: Yang, J., Fang, F., Sun, C. (eds) Intelligent Science and Intelligent Data Engineering. IScIDE 2012. Lecture Notes in Computer Science, vol 7751. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36669-7_29
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DOI: https://doi.org/10.1007/978-3-642-36669-7_29
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