Abstract
We propose a reinforcement learning approach to heating control in home automation, that can acquire a set of rules enabling an agent to heat a room to the desired temperature at a defined time while conserving as much energy as possible. Experimental results are presented that show the feasibility of our method. © 2013 Springer-Verlag Berlin Heidelberg.
Cite
CITATION STYLE
Zenger, A., Schmidt, J., & Krödel, M. (2013). Towards the intelligent home: Using reinforcement-learning for optimal heating control. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8077 LNAI, pp. 304–307). Springer Verlag. https://doi.org/10.1007/978-3-642-40942-4_30
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