Decaying active probing enables exact finite-step recovery of the interaction matrix in stable controllable linear-quadratic network games, with a reweighted sparse estimator achieving almost-sure consistency and finite-time support recovery under perturbations.
Learning quadratic games on networks
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Revealing Strategic Interactions in Network Games Under Decaying Active Probing
Decaying active probing enables exact finite-step recovery of the interaction matrix in stable controllable linear-quadratic network games, with a reweighted sparse estimator achieving almost-sure consistency and finite-time support recovery under perturbations.