Neural MMO is an open-source environment for agent-based intelligence research featuring large maps with large populations, long time horizons, and open-ended multi-task objectives. We propose a benchmark on this platform wherein participants train and submit agents to accomplish loosely specified goals -- both as individuals and as part of a team. The submitted agents are evaluated against thousands of other such user submitted agents. Participants get started with a publicly available code base for Neural MMO, scripted and learned baseline models, and training/evaluation/visualization packages. Our objective is to foster the design and implementation of algorithms and methods for adapting modern agent-based learning methods (particularly reinforcement learning) to a more general setting not limited to few agents, narrowly defined tasks, or short time horizons. Neural MMO provides a convenient setting for exploring these ideas without the computational inefficiency typically associated with larger environments.
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Fifteen-minute Competition Overview Video
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Overview
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SlidesLive Video » |
Joseph Suarez · Hanmo Chen 🔗 |