|
Abstract:
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.
|
