Juan I. Perotti, Orlando V. Billoni
In this work we study the problem of targeting signals in networks using entropy information measurements to quantify the cost of targeting. We introduce a penalization rule that impose a restriction to the long paths and therefore focus the signal to the target. By this scheme we goes continuously from fully random walkers to a walker biased to the target. We found that the optimal degree of penalization is mainly determined by the topology of the network. By mean of the analysis of several examples we have found that a small amount of penalization reduce considerably the typical walk length, and from this we conclude that a network can be efficiently navigated with restricted information.
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http://arxiv.org/abs/1202.5568
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