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Policy Improvement From Private Information For Decentralized LQG Teams
arXiv eess.SY0 views
arXiv:2610.15289v1 Announce Type: new Abstract: Sharing of information in multiagent systems allow for improved coordination. Delays in communication can cause asymmetries in information, causing classical results to fail. We study the decentralized LQG problem with delayed information. In general, the optimal policies are not linear and are difficult to calculate. Restricting to linear policies, we analytically calculate the gradient descent for gains from private information. This naturally lends itself to a gradient descent algorithm which we apply to examples to show policy improvements.
Source：https://arxiv.org/abs/2610.15289PreviousCo-Optimization of Scheduling, Control, and Incentivization of Electric Vehicles for Improving Power System StabilityNextAdaptive Event-Triggered Model Predictive Coverage Control with Average Update-Rate Regulation
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