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)

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.