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EnglishWe study the synthesis of optimal control policies for large-scalemulti-agent systems. The optimal control design induces a parsimonious controlintervention by means of l-1, sparsity-promoting control penalizations. Westudy instantaneous and infinite horizon sparse optimal feedback controllers.In order to circumvent the dimensionality issues associated to the control oflarge-scale agent-based models, we follow a Boltzmann approach. We generate(sub)optimal controls signals for the kinetic limit of the multi-agentdynamics, by sampling of the optimal solution of the associated two-agentdynamics. Numerical experiments assess the performance of the proposed sparsedesign.
| Titolo: | A Boltzmann approach to mean-field sparse feedback control |
| Autori: | |
| Data di pubblicazione: | 2017 |
| Abstract: | We study the synthesis of optimal control policies for large-scalemulti-agent systems. The optimal control design induces a parsimonious controlintervention by means of l-1, sparsity-promoting control penalizations. Westudy instantaneous and infinite horizon sparse optimal feedback controllers.In order to circumvent the dimensionality issues associated to the control oflarge-scale agent-based models, we follow a Boltzmann approach. We generate(sub)optimal controls signals for the kinetic limit of the multi-agentdynamics, by sampling of the optimal solution of the associated two-agentdynamics. Numerical experiments assess the performance of the proposed sparsedesign. |
| Handle: | http://hdl.handle.net/11562/972370 |
| Appare nelle tipologie: | 04.01 Contributo in atti di convegno |
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