PAC-Bayes framework derives high-probability performance bounds for learned controllers on unknown stochastic linear discrete-time systems and provides efficient algorithms for finite and infinite controller spaces.
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A PAC-Bayes Approach for Controlling Unknown Linear Discrete-time Systems
PAC-Bayes framework derives high-probability performance bounds for learned controllers on unknown stochastic linear discrete-time systems and provides efficient algorithms for finite and infinite controller spaces.