This work is a review of previous works on the stopping laws in networks. Among other results, we show a non combinatorial method to compute the stopping law, the existence of a minimal Markov chain without oversized information, the existence of a polynomial algorithm which projects the Markov chain onto the minimal Markov chain. Several applied examples are presented.
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Aletti, G., Saada, D. (2009). How to Reduce Unnecessary Noise in Targeted Networks. In: Naimzada, A.K., Stefani, S., Torriero, A. (eds) Networks, Topology and Dynamics. Lecture Notes in Economics and Mathematical Systems, vol 613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68409-1_9
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