Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning Algorithms

arXiv:2311.18736v2 Announce Type: replace-cross
Abstract: We introduce controlgym, a library of thirty-six industrial control settings, and ten infinite-dimensional partial differential equation (PDE)-based control problems. Integrated within the OpenAI Gym/Gymnasium (Gym) framework, controlgym allows direct applications of standard reinforcement learning (RL) algorithms like stable-baselines3. Our control environments complement those in Gym with continuous, unbounded action and observation spaces, motivated by real-world control applications. Moreover, the PDE control environments uniquely allow the users to extend the state dimensionality of the system to …

algorithms arxiv benchmarking control cs.ai cs.ce cs.lg cs.sy eess.sy environments math.oc reinforcement reinforcement learning scale type