We introduce Voyager, the first LLM-powered embodied lifelong learning agent
in Minecraft that continuously explores the world, acquires diverse skills, and
makes novel discoveries without human intervention. Voyager consists of three
key components: 1) an automatic curriculum that maximizes exploration, 2) an
ever-growing skill library of executable code for storing and retrieving
complex behaviors, and 3) a new iterative prompting mechanism that incorporates
environment feedback, execution errors, and self-verification for program
improvement. Voyager interacts with GPT-4 via blackbox queries, which bypasses
the need for model parameter fine-tuning. The skills developed by Voyager are
temporally extended, interpretable, and compositional, which compounds the
agent's abilities rapidly and alleviates catastrophic forgetting. Empirically,
Voyager shows strong in-context lifelong learning capability and exhibits
exceptional proficiency in playing Minecraft. It obtains 3.3x more unique
items, travels 2.3x longer distances, and unlocks key tech tree milestones up
to 15.3x faster than prior SOTA. Voyager is able to utilize the learned skill
library in a new Minecraft world to solve novel tasks from scratch, while other
techniques struggle to generalize. We open-source our full codebase and prompts
at this https URL

论文介绍了 Voyager：基于 LLM 的具身化终身学习代理，其由自动课程、可执行代码的技能库和新的迭代提示机制组成，可以在 Minecraft 中探索世界、获得多种技能和进行创新发现。在实证研究中，Voyager 表现出强大的上下文终身学习能力，在 Minecraft 游戏中比其他技术更快地解锁关键技术树里程碑，开发者在 https URL 上公开了代码库和提示。