This paper proposes a novel reinforcement learning (RL) architecture for the efficient scheduling and control of the heating, ventilation and air ...

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 ...

Incorporating RL controllers into HVAC systems has proven to significantly enhance energy efficiency and cost reduction, outperforming traditional control ...

Jun 18, 2017 ¡¤ In this work, we develop a data-driven ap- proach that leverages the deep reinforcement learning (DRL) technique, to intelligently learn the ...

In this work, we develop a data-driven approach that leverages the deep reinforcement learning (DRL) technique, to intelligently learn the effective strategy ...

Deep reinforcement learning (DRL) has shown immense potential for high-performing control in a variety of simulated settings, but has not been widely deployed ...

This repository provides a solution for training a reinforcement learning (RL) agent to perform temperature control in a room.

Jun 29, 2023 ¡¤ Due to the complex and uncertain nature of HVAC systems, we leverage a reinforcement learning (RL)-based controller to schedule the total power ...

Nov 26, 2020 ¡¤ Msc thesis presentation by Ilmari Vikström, Aalto University. Thesis Title: Deep ...
Duration: 21:33
Posted: Nov 26, 2020

Reinforcement Learning (RL) has improved upon traditional control methods in increasing the energy efficiency of HVAC systems. ... On the other hand, batch RL ...