Reinforcement Learning for Intensity Control: An Application to Choice-Based Network Revenue Management

ArXi:2406.05358v3 Announce Type: replace Intensity control is a class of continuous-time dynamic optimization problems with many important applications in Operations Research including queueing and revenue management. In this study, we propose a practical continuous-time reinforcement learning framework for intensity control using choice-based network revenue management as a, which is a classical problem in revenue management that features a large state space, a large action space, and a continuous time horizon.