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.
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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