Voyager minedojo is an AI tool that operates in the Minecraft environment, utilizing large language models to achieve lifelong learning without human intervention. It consists of three main components: an automatic curriculum, a skill library, and an iterative prompting mechanism.
The automatic curriculum maximizes exploration by generating tasks based on the agent’s progress and state. It aims to discover diverse things, similar to an in-context novelty search. This allows Voyager to continuously explore and uncover new aspects of the Minecraft world.
The skill library stores and retrieves complex behaviors, with each skill indexed by the embedding of its description. This enables easy retrieval of skills in similar situations. By synthesizing simpler programs, Voyager can enhance its capabilities over time and prevent catastrophic forgetting.
The iterative prompting mechanism incorporates environment feedback, execution errors, and self-verification to improve program execution. Voyager learns from its mistakes and refines its skills, enabling continuous improvement and adaptation.
Voyager interacts with GPT-4, a large language model, through blackbox queries, eliminating the need for fine-tuning of model parameters. This seamless integration allows Voyager to leverage the power of language models without extensive manual adjustments.
In experiments, Voyager demonstrates exceptional proficiency in playing Minecraft and showcases strong lifelong learning capabilities. It outperforms previous state-of-the-art approaches by obtaining more unique items, covering longer distances, and achieving key milestones in the tech tree at a faster rate. Additionally, Voyager excels in generalizing to novel tasks in new Minecraft worlds, surpassing other techniques and baseline methods.
Overall, Voyager minedojo combines the power of large language models with embodied learning to create an agent capable of continuous exploration, skill development, and novel discoveries in open-ended environments like Minecraft.