Durst, SebastianSebastianDurstBrüggenwirth, StefanStefanBrüggenwirth2022-03-142022-03-142021https://publica.fraunhofer.de/handle/publica/41181610.1109/RadarConf2147009.2021.9455234An 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.en621conference paper