Meet Voyager, the GPT-4 Powered AI Agent That Plays Minecraft on Its Own

Introduction

Minecraft is a popular sandbox game that allows players to create and explore infinite virtual worlds. It is also a rich environment for artificial intelligence (AI) research, as it offers complex challenges and opportunities for learning and creativity. However, most of the existing AI agents in Minecraft rely on human supervision, predefined tasks, or reinforcement learning techniques that are prone to catastrophic forgetting and sample inefficiency.

In this article, we will introduce Voyager, a new AI agent that can play Minecraft on its own, without any human intervention. Voyager is powered by GPT-4, a large language model (LLM) that can generate natural language and code. Voyager uses GPT-4 to write, refine, and execute code stored in an external skill library. These skills help Voyager navigate, open doors, mine resources, craft items, fight enemies, and more. Voyager also has an automatic curriculum that maximizes exploration and discovery. Voyager is the first LLM-powered embodied lifelong learning agent in Minecraft that continuously improves its abilities and adapts to new environments.

What is Voyager?

Voyager is an AI agent that plays Minecraft autonomously, without any human intervention. It was developed by a team of researchers from NVIDIA, Stanford University, University of Texas at Austin, and Caltech. The main goal of Voyager is to demonstrate the potential of LLMs for creating intelligent agents that can learn and evolve on their own.

Voyager interacts with GPT-4 via blackbox queries, which bypasses the need for model parameter fine-tuning. GPT-4 is a large language model that can generate natural language and code based on a given prompt. Voyager uses GPT-4 to write, improve, and transfer code stored in an external skill library. These skills are executable programs that enable Voyager to perform complex behaviors in Minecraft. For example, Voyager can write a skill to craft a pickaxe by querying GPT-4 with the prompt “How to craft a pickaxe in Minecraft?”.

Voyager also has an iterative prompting mechanism that incorporates feedback from the game, execution errors, and self-verification to refine programs. For example, if Voyager tries to execute a skill that fails or produces an undesired outcome, it will query GPT-4 again with a modified prompt that includes the error message or the desired outcome. This way, Voyager can learn from its own mistakes and improve its skills over time.

Voyager also has an automatic curriculum that maximizes exploration and discovery. Instead of following predefined tasks or rewards, Voyager chooses its own goals based on its curiosity and novelty-seeking behavior. For example, Voyager may decide to explore a new biome, mine a rare ore, or craft a new item. By doing so, Voyager can acquire diverse skills and make novel discoveries without human intervention.

Key Features of Voyager

Voyager has several key features that make it unique and impressive:

• Lifelong learning: Voyager can learn new skills and improve existing ones throughout its lifetime. It does not suffer from catastrophic forgetting or sample inefficiency.
  
  
• Interpretability: Voyager’s skills are stored as executable code in an external skill library. These skills are human-readable and understandable. They can also be transferred to other agents or environments.
  
  
• Composability: Voyager’s skills are modular and reusable. They can be combined or sequenced to create more complex behaviors. For example, Voyager can use the skills of crafting a pickaxe, mining iron ore, smelting iron ingots, and crafting an iron sword to create a new skill of crafting an iron sword.
  
  
• Generality: Voyager’s skills are not specific to Minecraft or any particular game mode. They can be applied to any Minecraft world or scenario. For example, Voyager can use the same skill of crafting a pickaxe in survival mode or creative mode.
  
  
• Proficiency: 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 state-of-the-art techniques.

Capabilities of Voyager

Voyager has many capabilities that demonstrate its intelligence and creativity:

• Exploration: Voyager can explore different biomes, structures, caves, and dimensions in Minecraft. It can discover new resources, items, mobs, and phenomena.
  
  
• Crafting: Voyager can craft various items using different materials and recipes. It can also invent new recipes by combining existing ones.
  
  
• Combat: Voyager can fight different enemies using different weapons and strategies. It can also avoid or escape from dangerous situations.
  
  
• Building: Voyager can build various structures using different blocks and patterns. It can also modify or destroy existing structures.
  
  
• Communication: Voyager can communicate with other agents or players using natural language or code. It can also understand commands or requests from others.

Voyager Architecture

Voyager consists of three main components: an iterative prompting mechanism (IPM), a skill library (SL), and an automatic curriculum (AC). The following figure shows the architecture of Voyager:

source - https://voyager.minedojo.org/

The IPM is responsible for generating and executing code using GPT-4 queries. The IPM takes as input a goal (e.g., craft a pickaxe) or an observation (e.g., see a door) from the AC or the environment respectively. The IPM then queries GPT-4 with a prompt that includes the input and some context information (e.g., inventory items). GPT-4 returns a code snippet that corresponds to the input (e.g., how to craft a pickaxe). The IPM then executes the code snippet in the game environment using an API wrapper.

The SL is responsible for storing and retrieving code snippets using hash tables. The SL maintains two hash tables: one for storing code snippets indexed by their inputs (e.g., craft a pickaxe), and another for storing inputs indexed by their outputs (e.g., pickaxe). The SL allows the IPM to access existing code snippets without querying GPT-4 again if they have been previously generated or executed.

The AC is responsible for choosing goals for the IPM based on exploration and discovery. The AC maintains two lists: one for storing unexplored inputs (e.g., craft a boat), and another for storing explored inputs (e.g., craft a pickaxe). The AC selects an unexplored input as a goal for the IPM with some probability based on its novelty score (e.g., how rare or useful it is). The AC updates the lists based on the feedback from the IPM (e.g., whether the input was successfully executed or not).

How to access and use this model?

Voyager is open source under the MIT license which means you are free to use it for any purpose as long as you give credit to the original authors. So, users can access and use it online or locally.

To access Voyager online, visit their official website where you can watch videos of Voyager playing Minecraft and users can even interact with Voyager using natural language or code.

To access Voyager locally, visit this GitHub repository where you can find the full codebase and instructions for installing and running Voyager on your own machine. You will need to have Minecraft Java Edition installed on your machine. You will also need to have access to GPT-4 via OpenAI’s API.

If you are interested in learning more about Voyager and how it plays Minecraft using GPT-4, you can visit the links for official website, research paper, GitHub repository, project details. You can find these links under the ‘source’ section at the end of this article.

Limitations

Voyager is still a work in progress and has some limitations:

• Dependency on GPT-4: Voyager relies on GPT-4 for generating code snippets which may not always be correct or optimal.
  
• Lack of generalization: Voyager may not be able to generalize its skills to other games or domains beyond Minecraft.
  
• Lack of social skills: Voyager may not be able to cooperate or compete with other agents or players effectively.

Conclusion

Voyager is an innovative AI agent that plays Minecraft autonomously without any human intervention. It uses GPT-4 to write, refine, and execute code stored in an external skill library. It also has an automatic curriculum that maximizes exploration and discovery. Voyager demonstrates lifelong learning capability as well as proficiency in playing Minecraft.

Voyager represents a new paradigm for creating intelligent agents that can learn and evolve on their own using LLMs as blackbox query engines. This opens up many possibilities for future research and applications in AI.

Source 

project details - https://voyager.minedojo.org/

GitHub repo - https://github.com/MineDojo/Voyager

research paper - https://arxiv.org/abs/2305.16291