Online Deep Reinforcement Learning for Stochastic Queuing Network Optimization

This work proposes an intervention-assisted framework that combines the learning power of neural networks with the guaranteed stability of classical control policies to enable online deep reinforcement learning for stochastic queuing network optimization.