NETEVOLVE: Social Network Forecasting using Multi-Agent Reinforcement Learning with Interpretable Features. Miyake, K., Ito, H., Faloutsos, C., Matsumoto, H., & Morishima, A. In Chua, T., Ngo, C., Kumar, R., Lauw, H. W., & Lee, R. K., editors, Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024, pages 2542–2551, 2024. ACM.
NETEVOLVE: Social Network Forecasting using Multi-Agent Reinforcement Learning with Interpretable Features [link]Paper  doi  bibtex   
@inproceedings{DBLP:conf/www/MiyakeIFMM24,
  author       = {Kentaro Miyake and
                  Hiroyoshi Ito and
                  Christos Faloutsos and
                  Hirotomo Matsumoto and
                  Atsuyuki Morishima},
  editor       = {Tat{-}Seng Chua and
                  Chong{-}Wah Ngo and
                  Ravi Kumar and
                  Hady W. Lauw and
                  Roy Ka{-}Wei Lee},
  title        = {{NETEVOLVE:} Social Network Forecasting using Multi-Agent Reinforcement
                  Learning with Interpretable Features},
  booktitle    = {Proceedings of the {ACM} on Web Conference 2024, {WWW} 2024, Singapore,
                  May 13-17, 2024},
  pages        = {2542--2551},
  publisher    = {{ACM}},
  year         = {2024},
  url          = {https://doi.org/10.1145/3589334.3647982},
  doi          = {10.1145/3589334.3647982},
  timestamp    = {Sun, 19 Jan 2025 13:10:07 +0100},
  biburl       = {https://dblp.org/rec/conf/www/MiyakeIFMM24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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