DocumentCode :
3726536
Title :
A Policy Gradient with Parameter-Based Exploration Approach for Zone-Heating
Author :
Kevin Van Vaerenbergh;Yann-Micha?l De ;Bruno Depraetere;Kristof Van Moffaert; Now?
Author_Institution :
Artificial Intell. Lab., Vrije Univ. Brussel, Brussels, Belgium
fYear :
2015
Firstpage :
556
Lastpage :
563
Abstract :
Heating a home is an energy consuming task. Most thermostats are programmed to turn on the heating at a particular time in order to reach and maintain a predefined target temperature. A lot of energy is wasted if these thermostats are not configured optimally since most of these thermostats do not take energy consumption into account but are only concerned with reaching the target temperature. In this paper we present a learning approach based on policy gradient with parameter estimations to balance user comfort with energy consumption. Our results show that our approach is capable of offering good trade-off solutions between these objectives.
Keywords :
"Heating","Learning (artificial intelligence)","Thermostats","Energy consumption","Aerospace electronics","Probability distribution"
Publisher :
ieee
Conference_Titel :
Computational Intelligence, 2015 IEEE Symposium Series on
Print_ISBN :
978-1-4799-7560-0
Type :
conf
DOI :
10.1109/SSCI.2015.88
Filename :
7376661
Link To Document :
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