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AssigneeVMware, Inc.
InventorsDev Nag, Yanislav Yankov, Dongni Wang, Gregory T. Burk, Nicholas Mark Grant Stephen
Estimating the term…
The current document is directed to methods and systems for simulation-based training of automated reinforcement-learning-based application managers. Simulators are generated from data collected from controlled computing environments controlled and may employ any of a variety of different machine-learning models to learn state-transition and reward models. The current disclosed methods and systems provide facilities for visualizing aspects of the models learned by a simulator and for initializing simulator models using domain information. In addition, the currently disclosed simulators employ weighted differences computed from simulator-generated and training-data state transitions for feedback to the machine-learning models to address various biases and deficiencies of commonly employed difference metrics in the context of training automated reinforcement-learning-based application managers.
A simulation manager that generates and trains simulators that are used to train automated reinforcement-learning-based application managers, the simulation manager comprising:
A method for training an automated reinforcement-learning-based application manager, the method comprising:
A physical data-storage device encoded with computer instructions that, when executed by one or more processors of a computer system that implements a simulation manager having one or more processors, one or more memories, one or more data-storage devices, and one or more communications subsystems, controls the simulation manager to:
Dependencies are inferred from the claim text.