On the Optimal Control of Opinion Dynamics on Evolving Networks
In this work we are interested in the modelling and control of opinion dynamics spreading on a time evolving network with scale-free asymptotic degree distribution. The mathematical model is formulated as a coupling of an opinion alignment system with a probabilistic description of the network. The optimal control problem aims at forcing consensus over the network, to this goal a control strategy based on the degree of connection of each agent has been designed. A numerical method based on a model predictive strategy is then developed and different numerical tests are reported. The results show that in this way it is possible to drive the overall opinion toward a desired state even if we control only a suitable fraction of the nodes.
KeywordsMulti-agent systems Consensus dynamics Scale-free networks Collective behavior Model predictive control
GA acknowledges the support of the ERC-Starting Grant project High-Dimensional Sparse Optimal Control (HDSPCONTR).
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