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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2508.12524 |
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| _version_ | 1866916904840462336 |
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| author | Suárez, Joseph Choe, Kyoung Whan Bloomin, David Gao, Jianming Li, Yunkun Feng, Yao Pola, Saidinesh Zhang, Kun Zhu, Yonghui Pinnaparaju, Nikhil Li, Hao Xiang Kanna, Nishaanth Scott, Daniel Sullivan, Ryan Shuman, Rose S. de Alcântara, Lucas Bradley, Herbie You, Kirsty Wu, Bo Jiang, Yuhao Li, Qimai Chen, Jiaxin Castricato, Louis Zhu, Xiaolong Isola, Phillip |
| author_facet | Suárez, Joseph Choe, Kyoung Whan Bloomin, David Gao, Jianming Li, Yunkun Feng, Yao Pola, Saidinesh Zhang, Kun Zhu, Yonghui Pinnaparaju, Nikhil Li, Hao Xiang Kanna, Nishaanth Scott, Daniel Sullivan, Ryan Shuman, Rose S. de Alcântara, Lucas Bradley, Herbie You, Kirsty Wu, Bo Jiang, Yuhao Li, Qimai Chen, Jiaxin Castricato, Louis Zhu, Xiaolong Isola, Phillip |
| contents | We present the results of the NeurIPS 2023 Neural MMO Competition, which attracted over 200 participants and submissions. Participants trained goal-conditional policies that generalize to tasks, maps, and opponents never seen during training. The top solution achieved a score 4x higher than our baseline within 8 hours of training on a single 4090 GPU. We open-source everything relating to Neural MMO and the competition under the MIT license, including the policy weights and training code for our baseline and for the top submissions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_12524 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Results of the NeurIPS 2023 Neural MMO Competition on Multi-task Reinforcement Learning Suárez, Joseph Choe, Kyoung Whan Bloomin, David Gao, Jianming Li, Yunkun Feng, Yao Pola, Saidinesh Zhang, Kun Zhu, Yonghui Pinnaparaju, Nikhil Li, Hao Xiang Kanna, Nishaanth Scott, Daniel Sullivan, Ryan Shuman, Rose S. de Alcântara, Lucas Bradley, Herbie You, Kirsty Wu, Bo Jiang, Yuhao Li, Qimai Chen, Jiaxin Castricato, Louis Zhu, Xiaolong Isola, Phillip Machine Learning We present the results of the NeurIPS 2023 Neural MMO Competition, which attracted over 200 participants and submissions. Participants trained goal-conditional policies that generalize to tasks, maps, and opponents never seen during training. The top solution achieved a score 4x higher than our baseline within 8 hours of training on a single 4090 GPU. We open-source everything relating to Neural MMO and the competition under the MIT license, including the policy weights and training code for our baseline and for the top submissions. |
| title | Results of the NeurIPS 2023 Neural MMO Competition on Multi-task Reinforcement Learning |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2508.12524 |