We present Meta MMO, a collection of many-agent minigames for use as a reinforcement learning benchmark. Meta MMO is built on top of Neural MMO, a massively multiagent environment that has been the subject of two previous NeurIPS competitions. Our work expands Neural MMO with several computationally efficient minigames. We explore generalization across Meta MMO by learning to play several minigames with a single set of weights. We release the environment, baselines, and training code under the MIT license. We hope that Meta MMO will spur additional progress on Neural MMO and, more generally, will serve as a useful benchmark for many-agent generalization.

翻译：我们提出了Meta MMO，这是一个用于强化学习基准测试的多智能体小游戏集合。Meta MMO基于Neural MMO构建，后者是一个大规模多智能体环境，曾作为前两届NeurIPS竞赛的主题。我们的工作通过引入若干计算高效的小游戏扩展了Neural MMO。我们探索了在Meta MMO上的泛化能力，通过使用单一参数集合学习多个小游戏。我们以MIT许可证发布了该环境、基线模型及训练代码。我们希望Meta MMO能推动Neural MMO的进一步进展，并更广泛地作为多智能体泛化研究的有用基准。