  An intelligent radar resource management is an essential milestone in the
development of a cognitive radar system. The quality of service based resource
allocation model (Q-RAM) is a framework allowing for intelligent decision
making but classical solutions seem insufficient for real-time application in a
modern radar system. In this paper, we present a solution for the Q-RAM radar
resource management problem using deep reinforcement learning considerably
improving on runtime performance.
