Jan 11, 2024 ¡¤ This paper provides a critical and reproducible evaluation, in terms of comfort and energy consumption, of several state-of-the-art DRL algorithms for HVAC ...

Jun 13, 2024 ¡¤ This paper provides a critical and reproducible evaluation, in terms of comfort and energy consumption, of several state-of-the-art DRL algorithms for HVAC ...

Jul 19, 2024 ¡¤ The study examines the controllers' robustness, adaptability, and trade-off between optimization goals by using the Sinergym framework. The ...

Sep 15, 2021 ¡¤ This paper conducts experiments to evaluate four actor-critic algorithms in a simulated data centre.

This paper provides a critical and reproducible evaluation, in terms of comfort and energy consumption, of several state-of-the-art DRL algorithms for HVAC ...

An experimental evaluation of deep reinforcement learning algorithms for HVAC control. https://doi.org/10.1007/s10462-024-10819-x.

This paper provides a comprehensive and standardized evaluation of several state-of-the-art DRL algorithms for HVAC control. The results confirm the potential ...

Aug 15, 2024 ¡¤ To this end, this paper comprehensively evaluates the strengths and limitations of state-of-the-art offline RL algorithms by conducting ...

Jun 13, 2024 ¡¤ Our paper "An experimental evaluation of Deep Reinforcement Learning algorithms for HVAC control" has been published in the journal ...

Jun 15, 2024 ¡¤ Our paper "An experimental evaluation of Deep Reinforcement Learning algorithms for HVAC control" has been published in the journal ...