Consensus and influence power approximation in time‐varying and directed networks subject to perturbations
Summary The paper focuses on the analysis of multi‐agent systems interacting over directed and time‐varying networks in presence of parametric uncertainty on the interaction weights. We assume that agents reach a consensus, and the main goal of this work is to characterize the contribution that each...
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Published in | International journal of robust and nonlinear control Vol. 29; no. 11; pp. 3485 - 3501 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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Abstract | Summary
The paper focuses on the analysis of multi‐agent systems interacting over directed and time‐varying networks in presence of parametric uncertainty on the interaction weights. We assume that agents reach a consensus, and the main goal of this work is to characterize the contribution that each agent has to the consensus value. This information is important for network intervention applications such as targeted advertising over social networks. Indeed, for an advertising campaign to be efficient, it has to take into account the influence power of each agent in the graph (ie, the contribution of each agent to the final consensus value). In our first results, we analytically describe the trajectory of the overall network, and we provide lower and upper bounds on the corresponding consensus value. We show that under appropriate assumptions, the contribution of each agent to the consensus value is smooth both in time and in the variation of the uncertainty parameter. This allows approximating the contribution of each agent when small perturbations affect the influence of each agent on its neighbors. Finally, we provide a numerical example to illustrate how our theoretical results apply in the context of network intervention. |
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AbstractList | Summary
The paper focuses on the analysis of multi‐agent systems interacting over directed and time‐varying networks in presence of parametric uncertainty on the interaction weights. We assume that agents reach a consensus, and the main goal of this work is to characterize the contribution that each agent has to the consensus value. This information is important for network intervention applications such as targeted advertising over social networks. Indeed, for an advertising campaign to be efficient, it has to take into account the influence power of each agent in the graph (ie, the contribution of each agent to the final consensus value). In our first results, we analytically describe the trajectory of the overall network, and we provide lower and upper bounds on the corresponding consensus value. We show that under appropriate assumptions, the contribution of each agent to the consensus value is smooth both in time and in the variation of the uncertainty parameter. This allows approximating the contribution of each agent when small perturbations affect the influence of each agent on its neighbors. Finally, we provide a numerical example to illustrate how our theoretical results apply in the context of network intervention. The paper focuses on the analysis of multi‐agent systems interacting over directed and time‐varying networks in presence of parametric uncertainty on the interaction weights. We assume that agents reach a consensus, and the main goal of this work is to characterize the contribution that each agent has to the consensus value. This information is important for network intervention applications such as targeted advertising over social networks. Indeed, for an advertising campaign to be efficient, it has to take into account the influence power of each agent in the graph (ie, the contribution of each agent to the final consensus value). In our first results, we analytically describe the trajectory of the overall network, and we provide lower and upper bounds on the corresponding consensus value. We show that under appropriate assumptions, the contribution of each agent to the consensus value is smooth both in time and in the variation of the uncertainty parameter. This allows approximating the contribution of each agent when small perturbations affect the influence of each agent on its neighbors. Finally, we provide a numerical example to illustrate how our theoretical results apply in the context of network intervention. The paper focuses on the analysis of multi-agent systems interacting over directed and time-varying networks in presence of parametric uncertainty on the interaction weights. We assume that agents reach a consensus and the main goal of this work is to characterize the contribution that each agent has to the consensus value. This information is important for network intervention applications such as targeted advertising over social networks. Indeed, for an advertising campaign to be efficient, it has to take into account the influence power of each agent in the graph (i.e., the contribution of each agent to the final consensus value). In our first results we analytically describe the trajectory of the overall network and we provide lower and upper bounds on the corresponding consensus value. We show that under appropriate assumptions, the contribution of each agent to the consensus value is smooth both in time and in the variation of the uncertainty parameter. This allows approximating the contribution of each agent when small perturbations affect the influence of each agent on its neighbors. Finally, we provide a numerical example to illustrate how our theoretical results apply in the context of network intervention. |
Author | Nešić, D. Morărescu, I.‐C. Martin, S. |
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Cites_doi | 10.1145/1772690.1772790 10.1109/TAC.2018.2803114 10.1109/CDC.2017.8264227 10.1108/13563281111156853 10.1109/TAC.2015.2506262 10.1109/TAC.2005.846556 10.1016/j.automatica.2015.11.030 10.1016/j.laa.2004.12.014 10.1109/TAC.2015.2492058 10.1109/TAC.2004.834113 10.1109/TAC.2010.2095315 10.1080/01621459.1974.10480137 10.1007/978-1-4612-0117-5 10.1109/TAC.2009.2033750 10.1016/j.automatica.2012.09.025 10.1109/TAC.2012.2203214 10.1109/TAC.2004.841888 10.1002/rnc.3764 10.1109/CDC.2017.8263709 10.1137/11083438X |
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The paper focuses on the analysis of multi‐agent systems interacting over directed and time‐varying networks in presence of parametric uncertainty on... The paper focuses on the analysis of multi‐agent systems interacting over directed and time‐varying networks in presence of parametric uncertainty on the... The paper focuses on the analysis of multi-agent systems interacting over directed and time-varying networks in presence of parametric uncertainty on the... |
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SubjectTerms | Advertising Automatic Control Engineering Computer Science linear perturbed systems Parameter uncertainty robustness Social networks time‐varying consensus Trajectory analysis uncertain systems Upper bounds |
Title | Consensus and influence power approximation in time‐varying and directed networks subject to perturbations |
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