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Network Learning in Quadratic Games from Fictitious Plays
Next, in view of the inherent stability and sparsity constraints for the network interaction structure, we propose a stable and sparse system identification framework for learning the interaction graph from full player action observations.
Privacy-Preserving Push-sum Average Consensus via State Decomposition
That is to say, only the exchanged substate would be visible to an adversary, preventing the initial state information from leakage.
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