Mar 15, 2024 ， This paper compares three different RL approaches to HVAC optimization: one based on a black-box system identification model trained on historical data.
Highlights. •. HVAC optimization with reinforcement learning algorithms. •. Assessment and comparison of three different approaches. •. Online approach with ...
Aug 2, 2024 ， This study proposes a self-learning control system that aims to learn occupancy profiles, building energy consumption patterns, and lag-time of ...
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Brandi, Deep reinforcement learning to optimise indoor temperature control and heating energy consumption in buildings, Energy and Buildings, ∇ 224 ， Drgoňa, All ...
Dec 8, 2022 ， We present a systematic approach to accelerate online reinforcement learning for HVAC control by taking full advantage of the knowledge from domain experts in ...
Jun 18, 2017 ， In [6], the authors propose a neural fitted RL method through the interaction with ten- ants to determine the optimal temperature setting point.
Missing: online | Show results with:online
A deep reinforcement learning approach to using whole building energy model for hvac optimal control. In 2018 Building Performance Analysis. Conference and ...
A novel state action space formalism is proposed to enable a Reinforcement Learning agent to successfully control the HVAC system by optimising both occupant ...
The RL approach is essentially an optimization tool used to identify the optimal decision-making strategy that maximizes the overall accumulated benefit in a ...
Dec 12, 2022 ， In this work, we present a systematic approach to accelerate online reinforcement learning for HVAC control by taking full advantage of the ...
