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Reinforcement Learning for Decentralized Stochastic Control
We consider decentralized optimization of a controlled stochastic system where a finite number of decision makers seek to arrive at optimal policies using only local measurements and cost realizations. For such a context, ...
Networked Control Systems with Unbounded Noise under Information Constraints
We investigate the stabilization of unstable multidimensional partially observed single-station, multi-sensor (single-controller) and multi-controller (single-sensor) linear systems controlled over discrete noiseless ...