Minimax Exploiter: A Data Efficient Approach for Competitive Self-Play. Bairamian, D., Marcotte, P., Romoff, J., Robert, G., & Nowrouzezahrai, D. In Dastani, M., Sichman, J. S., Alechina, N., & Dignum, V., editors, Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2024, Auckland, New Zealand, May 6-10, 2024, pages 114–122, 2024. International Foundation for Autonomous Agents and Multiagent Systems / ACM.
Minimax Exploiter: A Data Efficient Approach for Competitive Self-Play [link]Paper  doi  bibtex   1 download  
@inproceedings{DBLP:conf/atal/BairamianMRRN24,
  author       = {Daniel Bairamian and
                  Philippe Marcotte and
                  Joshua Romoff and
                  Gabriel Robert and
                  Derek Nowrouzezahrai},
  editor       = {Mehdi Dastani and
                  Jaime Sim{\~{a}}o Sichman and
                  Natasha Alechina and
                  Virginia Dignum},
  title        = {Minimax Exploiter: {A} Data Efficient Approach for Competitive Self-Play},
  booktitle    = {Proceedings of the 23rd International Conference on Autonomous Agents
                  and Multiagent Systems, {AAMAS} 2024, Auckland, New Zealand, May 6-10,
                  2024},
  pages        = {114--122},
  publisher    = {International Foundation for Autonomous Agents and Multiagent Systems
                  / {ACM}},
  year         = {2024},
  url          = {https://dl.acm.org/doi/10.5555/3635637.3662858},
  doi          = {10.5555/3635637.3662858},
  timestamp    = {Wed, 26 Jun 2024 14:06:50 +0200},
  biburl       = {https://dblp.org/rec/conf/atal/BairamianMRRN24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

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