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Near-optimal Deep Reinforcement Learning Policies from Data for Zone Temperature Control

Near-optimal Deep Reinforcement Learning Policies from Data for Zone Temperature Control

L. D. Natale
B. Svetozarevic
Philipp Heer
Colin N. Jones
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Papers citing "Near-optimal Deep Reinforcement Learning Policies from Data for Zone Temperature Control"

5 / 5 papers shown
Title
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems
Truong X. Nghiem
Ján Drgoňa
Colin N. Jones
Zoltán Nagy
Roland Schwan
...
J. Paulson
Andrea Carron
M. Zeilinger
Wenceslao Shaw-Cortez
D. Vrabie
PINN
AI4CE
37
30
0
24 Jun 2023
Towards Scalable Physically Consistent Neural Networks: an Application to Data-driven Multi-zone Thermal Building Models
Towards Scalable Physically Consistent Neural Networks: an Application to Data-driven Multi-zone Thermal Building Models
L. D. Natale
B. Svetozarevic
Philipp Heer
Colin N. Jones
AI4CE
26
28
0
23 Dec 2022
Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules
Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules
L. D. Natale
B. Svetozarevic
Philipp Heer
Colin N. Jones
26
0
0
30 Nov 2022
Lessons Learned from Data-Driven Building Control Experiments: Contrasting Gaussian Process-based MPC, Bilevel DeePC, and Deep Reinforcement Learning
Lessons Learned from Data-Driven Building Control Experiments: Contrasting Gaussian Process-based MPC, Bilevel DeePC, and Deep Reinforcement Learning
L. D. Natale
Yingzhao Lian
E. Maddalena
Jicheng Shi
Colin N. Jones
16
18
0
31 May 2022
Physically Consistent Neural Networks for building thermal modeling: theory and analysis
Physically Consistent Neural Networks for building thermal modeling: theory and analysis
L. D. Natale
B. Svetozarevic
Philipp Heer
Colin N. Jones
PINN
AI4CE
57
84
0
06 Dec 2021