Voyager

Voyager

Voyager: The First LLM-Powered Embodied Lifelong Learning Agent

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Description:

Voyager is an embodied lifelong learning agent that continuously explores the world, acquires diverse skills, and makes novel discoveries without human intervention. It consists of three key components: an automatic curriculum that maximizes exploration, an ever-growing skill library of executable code for storing and retrieving complex behaviors, and 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.

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Features

Advantages

  • Continuously explores the world, acquires diverse skills, and makes novel discoveries without human intervention
  • Strong in-context lifelong learning capability
  • Exceptional proficiency in playing Minecraft
  • 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
  • Able to utilize the learned skill library in a new Minecraft world to solve novel tasks from scratch

Disadvantages

  • May require a lot of computational resources
  • May not be able to generalize to other games or tasks
  • May be difficult to debug

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