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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Auteurs principaux: Christian Blad, Simon Bøgh, Carsten Kallesøe
Format: article
Langue:EN
Publié: MDPI AG 2021
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Accès en ligne:https://doaj.org/article/8030b101c8894434b618d3475c0b545a
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