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Semi-analytical Industrial Cooling System Model for Reinforcement Learning
[article]
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
arXiv:2207.13131v1
fatcat:kesfk5km7vbztgkajkrwsn2hfi