Optimizing Admission Control while Ensuring Quality of Service in Multimedia Networks via Reinforcement Learning

Part of Advances in Neural Information Processing Systems 11 (NIPS 1998)

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Authors

Timothy Brown, Hui Tong, Satinder Singh

Abstract

This paper examines the application of reinforcement learning to a telecommunications networking problem . The problem requires that rev(cid:173) enue 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.