神经MMO 2.0:大规模多任务增强版大规模多智体学习
Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning
November 7, 2023
作者: Joseph Suárez, Phillip Isola, Kyoung Whan Choe, David Bloomin, Hao Xiang Li, Nikhil Pinnaparaju, Nishaanth Kanna, Daniel Scott, Ryan Sullivan, Rose S. Shuman, Lucas de Alcântara, Herbie Bradley, Louis Castricato, Kirsty You, Yuhao Jiang, Qimai Li, Jiaxin Chen, Xiaolong Zhu
cs.AI
摘要
神经MMO 2.0是一个用于强化学习研究的大规模多智能体环境。这个新版本的关键特性是一个灵活的任务系统,允许用户定义广泛的目标和奖励信号。我们挑战研究人员训练能够泛化到在训练过程中从未见过的任务、地图和对手的智能体。神经MMO具有128个智能体的程序生成地图,在标准设置下支持多达。2.0版本是其前身的完全重写,性能提高了三倍,并与CleanRL兼容。我们将该平台作为免费开源软件发布,提供详尽的文档,可在neuralmmo.github.io获取,并有一个活跃的社区Discord。为了激发对这一新平台的初步研究,我们同时在NeurIPS 2023举办一项竞赛。
English
Neural MMO 2.0 is a massively multi-agent environment for reinforcement
learning research. The key feature of this new version is a flexible task
system that allows users to define a broad range of objectives and reward
signals. We challenge researchers to train agents capable of generalizing to
tasks, maps, and opponents never seen during training. Neural MMO features
procedurally generated maps with 128 agents in the standard setting and support
for up to. Version 2.0 is a complete rewrite of its predecessor with three-fold
improved performance and compatibility with CleanRL. We release the platform as
free and open-source software with comprehensive documentation available at
neuralmmo.github.io and an active community Discord. To spark initial research
on this new platform, we are concurrently running a competition at NeurIPS
2023.