This paper examines the application of reinforcement learning to a telecommunications networking problem. The problem requires that revenue be maximized while simultaneously meeting a quality of service constraint that forbids entry into certain states. We present a general solution to this multi-criteria problem that is able to earn significantly higher revenues than alternatives.
['Timothy X. Brown', 'Hui Tong', 'Satinder P. Singh']
Optimizing Admission Control while Ensuring Quality of Service in Multimedia Networks via Reinforcement Learning