Semi-analytical Industrial Cooling System Model for Reinforcement Learning [article]

Yuri Chervonyi, Praneet Dutta, Piotr Trochim, Octavian Voicu, Cosmin Paduraru, Crystal Qian, Emre Karagozler, Jared Quincy Davis, Richard Chippendale, Gautam Bajaj, Sims Witherspoon, Jerry Luo
2022 arXiv   pre-print
We present a hybrid industrial cooling system model that embeds analytical solutions within a multi-physics simulation. This model is designed for reinforcement learning (RL) applications and balances simplicity with simulation fidelity and interpretability. The model's fidelity is evaluated against real world data from a large scale cooling system. This is followed by a case study illustrating how the model can be used for RL research. For this, we develop an industrial task suite that allows
more » ... pecifying different problem settings and levels of complexity, and use it to evaluate the performance of different RL algorithms.
arXiv:2207.13131v1 fatcat:kesfk5km7vbztgkajkrwsn2hfi