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We introduce Voyager, the first LLM-powered embodied lifelong learning agent in Minecraft that continuously explores the world, acquires diverse skills, and makes novel discoveries without human intervention. Voyager utilizes GPT-4 to bypass the need for model parameter fine-tuning and its skills 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. We open-source our full codebase and prompts at this https URL.

We introduce Voyager, the first LLM-powered embodied lifelong learning agent in Minecraft that continuously explores the world, acquires diverse skills, and makes novel discoveries without human intervention. Voyager consists of three key components: 1) an automatic curriculum that maximizes exploration, 2) an ever-growing skill library of executable code for storing and retrieving complex behaviors, and 3) 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. We open-source our full codebase and prompts at <a target="_blank" rel="noopener noreferrer nofollow" class="link-external link-https" href="https://voyager.minedojo.org/">this https URL</a>.What if we set GPT-4 free in Minecraft? I’m excited to announce Voyager, the first lifelong learning agent that plays Minecraft purely in-context. Voyager continuously improves itself by writing, refining, committing, and retrieving code from a skill library. GPT-4 unlocks a new paradigm: “training” is code execution rather than gradient descent. “Trained model” is a codebase of skills that Voyager iteratively composes, rather than matrices of floats. We are pushing no-gradient architecture to its limit. Voyager rapidly becomes a seasoned explorer. In Minecraft, it obtains 3.3× more unique items, travels 2.3× longer distances, and unlocks key tech tree milestones up to 15.3× faster than prior methods. We open-source everything. Let generalist agents emerge in Minecraft! Welcome you all to try today: <a target="_blank" rel="noopener noreferrer nofollow" href="https://voyager.minedojo.org">https://voyager.minedojo.org</a> Paper: <a target="_blank" rel="noopener noreferrer nofollow" href="https://arxiv.org/abs/2305.16291">https://arxiv.org/abs/2305.16291</a> Code: <a target="_blank" rel="noopener noreferrer nofollow" href="https://github.com/MineDojo/Voyag">https://github.com/MineDojo/Voyag</a>Voyager has 3 key components: 1) An iterative prompting mechanism that incorporates game feedback, execution errors, and self-verification to refine programs; 2) A skill library of code to store &amp; retrieve complex behaviors; 3) An automatic curriculum to maximize exploration.<a target="_blank" rel="noopener noreferrer nofollow" href="https://twitter.com/i/status/1662117785487704067">https://twitter.com/i/status/1662117785487704067</a>

 We introduce Voyager, the first LLM-powered embodied lifelong learning agent in Minecraft that continuously explores the world, acquires diverse skills, and makes novel discoveries without human intervention. Voyager consists of three key components: 1) an automatic curriculum that maximizes exploration, 2) an ever-growing skill library of executable code for storing and retrieving complex behaviors, and 3) 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. We open-source our full codebase and prompts at this https URL . What if we set GPT-4 free in Minecraft? I’m excited to announce Voyager, the first lifelong learning agent that plays Minecraft purely in-context . Voyager continuously improves itself by writing, refining, committing, and retrieving code from a skill library. GPT-4 unlocks a new paradigm: “training” is code execution rather than gradient descent. “Trained model” is a codebase of skills that Voyager iteratively composes, rather than matrices of floats. We are pushing no-gradient architecture to its limit. Voyager rapidly becomes a seasoned explorer. In Minecraft, it obtains 3.3× more unique items, travels 2.3× longer distances, and unlocks key tech tree milestones up to 15.3× faster than prior methods. We open-source everything . Let generalist agents emerge in Minecraft! Welcome you all to try today: https://voyager.minedojo.org Paper: https://arxiv.org/abs/2305.16291 Code: https://github.com/MineDojo/Voyag Voyager has 3 key components: 1) An iterative prompting mechanism that incorporates game feedback, execution errors, and self-verification to refine programs; 2) A skill library of code to store & retrieve complex behaviors; 3) An automatic curriculum to maximize exploration. https://twitter.com/i/status/1662117785487704067 We introduce Voyager, the first LLM-powered embodied lifelong learning agent in Minecraft that continuously explores the world, acquires diverse skills, and makes novel discoveries without human intervention. Voyager utilizes GPT-4 to bypass the need for model parameter fine-tuning and its skills 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. We open-source our full codebase and prompts at this https URL. 

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

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

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