How even tiny influence can have a big impact!

Barbara Keller; David Peleg; Roger Wattenhofer

doi:10.1007/978-3-319-07890-8_22

How even tiny influence can have a big impact!

Barbara Keller, David Peleg, Roger Wattenhofer

Department of Computer Science and Applied Mathematics

Weizmann Institute of Science

Research output: Contribution to conference › Paper › peer-review

Abstract

An influence network is a graph where each node changes its state according to a function of the states of its neighbors. We present bounds for the stabilization time of such networks. We derive a general bound for the classic "Democrats and Republicans" problem and study different model modifications and their influence on the way of stabilizing and their stabilization time. Our main contribution is an exponential lower and upper bound on weighted influence networks. We also investigate influence networks with asymmetric weights and show an influence network with an exponential cycle length in the stable situation. 2014 Springer International Publishing.

Original language	English
Pages	252-263
DOIs	https://doi.org/10.1007/978-3-319-07890-8_22
State	Published - 2014
Event	7th International Conference on Fun with Algorithms, FUN 2014 - Sicily Duration: 1 Jul 2014 → 1 Jul 2014

Conference

Conference	7th International Conference on Fun with Algorithms, FUN 2014
Period	1/07/14 → 1/07/14

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10.1007/978-3-319-07890-8_22

Cite this

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title = "How even tiny influence can have a big impact!",

abstract = "An influence network is a graph where each node changes its state according to a function of the states of its neighbors. We present bounds for the stabilization time of such networks. We derive a general bound for the classic {"}Democrats and Republicans{"} problem and study different model modifications and their influence on the way of stabilizing and their stabilization time. Our main contribution is an exponential lower and upper bound on weighted influence networks. We also investigate influence networks with asymmetric weights and show an influence network with an exponential cycle length in the stable situation. 2014 Springer International Publishing.",

author = "Barbara Keller and David Peleg and Roger Wattenhofer",

year = "2014",

doi = "10.1007/978-3-319-07890-8_22",

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AU - Keller, Barbara

AU - Peleg, David

AU - Wattenhofer, Roger

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AB - An influence network is a graph where each node changes its state according to a function of the states of its neighbors. We present bounds for the stabilization time of such networks. We derive a general bound for the classic "Democrats and Republicans" problem and study different model modifications and their influence on the way of stabilizing and their stabilization time. Our main contribution is an exponential lower and upper bound on weighted influence networks. We also investigate influence networks with asymmetric weights and show an influence network with an exponential cycle length in the stable situation. 2014 Springer International Publishing.

U2 - 10.1007/978-3-319-07890-8_22

DO - 10.1007/978-3-319-07890-8_22

M3 - محاضرة

SP - 252

EP - 263

T2 - 7th International Conference on Fun with Algorithms, FUN 2014

Y2 - 1 July 2014 through 1 July 2014

ER -

How even tiny influence can have a big impact!

Abstract

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