A Multi-Agent Reinforcement Learning Approach to Price and Comfort Optimization in HVAC-Systems
This paper addresses the challenge of minimizing training time for the control of Heating, Ventilation, and Air-conditioning (HVAC) systems with online Reinforcement Learning (RL). This is done by developing a novel approach to Multi-Agent Reinforcement Learning (MARL) to HVAC systems. In this paper...
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Autores principales: | Christian Blad, Simon Bøgh, Carsten Kallesøe |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/8030b101c8894434b618d3475c0b545a |
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