spiders); (3) continually explore the world and seek out new tasks in a self-driven manner.
Towards these goals, we introduce VOYAGER, the first LLM-powered embodied lifelong learning
agent to drive exploration, master a wide range of skills, and make new discoveries continually
without human intervention in Minecraft. VOYAGER is made possible through three key modules
(Fig. 2): 1) an automatic curriculum that maximizes exploration; 2) a skill library for storing
and retrieving complex behaviors; and 3) a new iterative prompting mechanism that generates
executable code for embodied control. We opt to use code as the action space instead of low-level
motor commands because programs can naturally represent temporally extended and compositional
actions [16, 22], which are essential for many long-horizon tasks in Minecraft. VOYAGER interacts
with a blackbox LLM (GPT-4 [35]) through prompting and in-context learning [36–38]. Our approach
VOYAGER- An Open-Ended Embodied Agent with Large Language Models