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This tutorial discusses the practical limitations of
reinforcement and deep learning methods in resource
management in nonstationary radio environments. We carefully
compare supervised (deep) and reinforcement learning models
to support rate maximization objectives under user mobility
based on the practical limitations.
reinforcement and deep learning methods in resource
management in nonstationary radio environments. We carefully
compare supervised (deep) and reinforcement learning models
to support rate maximization objectives under user mobility
based on the practical limitations.