MARLISA: Multi-Agent Reinforcement Learning with Iterative Sequential Action Selection for Load Shaping of Grid-Interactive Connected Buildings

José R. Vázquez-Canteli, Gregor Henze, Zoltán Nagy 0002. MARLISA: Multi-Agent Reinforcement Learning with Iterative Sequential Action Selection for Load Shaping of Grid-Interactive Connected Buildings. In BuildSys '20: The 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, Virtual Event, Japan, November 18-20, 2020. pages 170-179, ACM, 2020. [doi]

@inproceedings{Vazquez-Canteli20,
  title = {MARLISA: Multi-Agent Reinforcement Learning with Iterative Sequential Action Selection for Load Shaping of Grid-Interactive Connected Buildings},
  author = {José R. Vázquez-Canteli and Gregor Henze and Zoltán Nagy 0002},
  year = {2020},
  doi = {10.1145/3408308.3427604},
  url = {https://doi.org/10.1145/3408308.3427604},
  researchr = {https://researchr.org/publication/Vazquez-Canteli20},
  cites = {0},
  citedby = {0},
  pages = {170-179},
  booktitle = {BuildSys '20: The 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, Virtual Event, Japan, November 18-20, 2020},
  publisher = {ACM},
  isbn = {978-1-4503-8061-4},
}