Voyager: An Open-Ended Embodied Agent with Large Language Models

Introduction

Voyager represents a groundbreaking advancement in artificial intelligence, specifically designed for the Minecraft environment. As the first LLM-powered embodied lifelong learning agent, Voyager continuously explores, acquires diverse skills, and makes novel discoveries without human intervention. This innovative AI showcases the potential of combining large language models with interactive, open-world environments.

Key Components

Voyager's success is built upon three crucial elements:

1. Automatic Curriculum: Maximizes exploration and learning opportunities within the Minecraft world.
2. Ever-growing Skill Library: Stores and retrieves complex behaviors as executable code, allowing for rapid skill development and retention.
3. Iterative Prompting Mechanism: Incorporates environment feedback, execution errors, and self-verification for continuous program improvement.

Unique Features

• GPT-4 Integration: Voyager interacts with GPT-4 via blackbox queries, eliminating the need for model parameter fine-tuning.
• Temporally Extended Skills: Developed skills are interpretable and compositional, leading to rapid ability compounding.
• Catastrophic Forgetting Mitigation: The skill library approach helps alleviate the common AI challenge of forgetting previously learned information.

Performance and Capabilities

Empirical results demonstrate Voyager's exceptional proficiency in Minecraft:

• Obtains 3.3× more unique items than previous state-of-the-art agents
• Travels 2.3× longer distances, showcasing enhanced exploration abilities
• Unlocks key tech tree milestones up to 15.3× faster

Generalization and Adaptability

Voyager exhibits strong in-context lifelong learning capabilities:

• Successfully utilizes the learned skill library in new Minecraft worlds
• Solves novel tasks from scratch, demonstrating adaptability
• Outperforms other techniques that struggle with generalization

Technical Implementation

The Voyager codebase is available under the MIT License, providing researchers and developers with the opportunity to explore and build upon this groundbreaking AI agent.

Conclusion

Voyager represents a significant leap forward in embodied AI agents, showcasing the potential of combining large language models with interactive environments. Its ability to autonomously explore, learn, and adapt opens up new possibilities for AI applications in complex, open-ended worlds.