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. 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}
}
Downloads: 1
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