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Peer-reviewedCC BY-NC-ND 4.0Scientific Reports

Multi-agent deep reinforcement learning for resilient recovery of electric–gas coupled energy systems under extreme disasters

  • Pei Zhang
  • Chao Yang
  • Jinghui He
Open at sourcePDFDOICite

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Cite

BibTeXRIS
BibTeX
@article{zhang2026multiagent,
  title = {{Multi-agent deep reinforcement learning for resilient recovery of electric–gas coupled energy systems under extreme disasters}},
  author = {Pei Zhang and Chao Yang and Jinghui He},
  journal = {Scientific Reports},
  year = {2026},
  month = oct,
  doi = {10.1038/s41598-026-62933-1},
  url = {https://www.nature.com/articles/s41598-026-62933-1},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Multi-agent deep reinforcement learning for resilient recovery of electric–gas coupled energy systems under extreme disasters
AU  - Pei Zhang
AU  - Chao Yang
AU  - Jinghui He
PY  - 2026
DA  - 2026/10/08
JO  - Scientific Reports
DO  - 10.1038/s41598-026-62933-1
UR  - https://www.nature.com/articles/s41598-026-62933-1
SN  - 2045-2322
ER  -