The Pump Scheduling Problem: A Real-World Scenario for Reinforcement Learning. (arXiv:2210.11111v1 [cs.LG])

Deep Reinforcement Learning (DRL) has achieved remarkable success in
scenarios such as games and has emerged as a potential solution for control
tasks. That is due to its ability to leverage scalability and handle complex
dynamics. However, few works have targeted environments grounded in real-world
settings. Indeed, real-world scenarios can be challenging, especially when
faced with the high dimensionality of the state space and unknown reward
function. We release a testbed consisting of an environment simulator and
demonstrations of human …

arxiv reinforcement reinforcement learning scheduling