Abstract

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.

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Voyager discovers new Minecraft items and skills continually by self-driven exploration, significantly outperforming the baselines.

Introduction

Building generally capable embodied agents that continuously explore, plan, and develop new skills in open-ended worlds is a grand challenge for the AI community. Classical approaches employ reinforcement learning (RL) and imitation learning that operate on primitive actions, which could be challenging for systematic exploration, interpretability, and generalization. Recent advances in large language model (LLM) based agents harness the world knowledge encapsulated in pre-trained LLMs to generate consistent action plans or executable policies. They are applied to embodied tasks like games and robotics, as well as NLP tasks without embodiment. However, these agents are not lifelong learners that can progressively acquire, update, accumulate, and transfer knowledge over extended time spans.

Let us consider Minecraft as an example. Unlike most other games studied in AI, Minecraft does not impose a predefined end goal or a fixed storyline but rather provides a unique playground with endless possibilities. An effective lifelong learning agent should have similar capabilities as human players: (1) propose suitable tasks based on its current skill level and world state, e.g., learn to harvest sand and cactus before iron if it finds itself in a desert rather than a forest; (2) refine skills based on environment feedback and commit mastered skills to memory for future reuse in similar situations (e.g. fighting zombies is similar to fighting spiders); (3) continually explore the world and seek out new tasks in a self-driven manner.

Voyager Components

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: 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, which are essential for many long-horizon tasks in Minecraft. Voyager interacts with a blackbox LLM (GPT-4) through prompting and in-context learning. Our approach bypasses the need for model parameter access and explicit gradient-based training or finetuning.

Voyager consists of three key components: an automatic curriculum for open-ended exploration, a skill library for increasingly complex behaviors, and an iterative prompting mechanism that uses code as action space.

Automatic Curriculum

Automatic curriculum. The automatic curriculum takes into account the exploration progress and the agent's state to maximize exploration. The curriculum is generated by GPT-4 based on the overarching goal of "discovering as many diverse things as possible". This approach can be perceived as an in-context form of novelty search.

Skill Library

Skill library. Top: Adding a new skill. Each skill is indexed by the embedding of its description, which can be retrieved in similar situations in the future. Bottom: Skill retrieval. When faced with a new task proposed by the automatic curriculum, we perform querying to identify the top-5 relevant skills. Complex skills can be synthesized by composing simpler programs, which compounds Voyager's capabilities rapidly over time and alleviates catastrophic forgetting.

Iterative Prompting Mechanism

Left: Environment feedback. GPT-4 realizes it needs 2 more planks before crafting sticks. Right: Execution error. GPT-4 realizes it should craft a wooden axe instead of an acacia axe since there is no acacia axe in Minecraft.

Self-verification. By providing the agent's current state and the task to GPT-4, we ask it to act as a critic and inform us whether the program achieves the task. In addition, if the task fails, it provides a critique by suggesting how to complete the task.

Tachosoft Mileage Calculator Online Better <HD>

Tachosoft Mileage Calculator Online: A Comprehensive Review

Introduction

The Tachosoft Mileage Calculator is a popular online tool used to calculate vehicle mileage and track fuel efficiency. In this report, we will review the features and benefits of using the Tachosoft Mileage Calculator online and compare it with other similar tools.

Features of Tachosoft Mileage Calculator

Easy to Use: The Tachosoft Mileage Calculator has a user-friendly interface that allows users to easily input their vehicle's data and calculate mileage.
Accurate Calculations: The calculator uses advanced algorithms to provide accurate mileage calculations based on the input data.
Multiple Fuel Types: The calculator supports various fuel types, including gasoline, diesel, and hybrid.
Currency and Unit Conversions: The calculator allows users to convert mileage and fuel consumption to different currencies and units.

Benefits of Using Tachosoft Mileage Calculator

Improved Fuel Efficiency: The calculator helps users track their fuel efficiency and identify areas for improvement.
Cost Savings: By monitoring mileage and fuel consumption, users can optimize their routes and reduce fuel costs.
Environmental Benefits: The calculator promotes eco-friendly driving habits, which can help reduce carbon emissions.

Comparison with Other Online Mileage Calculators

| Feature | Tachosoft Mileage Calculator | FuelEconomy Calculator | MileageCalc | | --- | --- | --- | --- | | Ease of Use | 4.5/5 | 4/5 | 3.5/5 | | Accuracy of Calculations | 4.8/5 | 4.5/5 | 4/5 | | Multiple Fuel Types | 4.5/5 | 4/5 | 3.5/5 | | Currency and Unit Conversions | 4.5/5 | 4/5 | 3/5 | tachosoft mileage calculator online better

Conclusion

The Tachosoft Mileage Calculator online is a reliable and user-friendly tool for calculating vehicle mileage and tracking fuel efficiency. Its advanced features and benefits make it a better option compared to other online mileage calculators. However, there are areas for improvement, such as adding more fuel types and enhancing the user interface.

Recommendations

Enhance User Interface: Improve the user interface to make it more modern and intuitive.
Add More Fuel Types: Include more fuel types, such as electric and hydrogen fuel cell.
Integrate with Other Tools: Integrate the calculator with other tools, such as GPS tracking devices and vehicle maintenance software.

Rating

Overall Rating: 4.6/5

The Tachosoft Mileage Calculator online is a valuable tool for anyone looking to track their vehicle's mileage and fuel efficiency. Its accuracy, ease of use, and advanced features make it a top choice among online mileage calculators. Easy to Use : The Tachosoft Mileage Calculator

To make an online version of a TachoSoft Mileage Calculator better than the legacy desktop software, you should focus on accessibility, database depth, and automation. Key Features for a Superior Online Version Cloud-Based Vehicle Database

: Provide instant access to the latest algorithms for thousands of vehicle models without requiring manual software updates or patches. Hex/Dump Visualizer

: Integrate a built-in hex editor that allows users to upload their

files and see the mileage location highlighted in real-time, rather than just providing a static value. Automatic Algorithm Matching

: Implement a feature that detects the vehicle's EEPROM/MCU type from the uploaded dump and automatically suggests the correct calculation algorithm. Multi-Unit Conversion : Allow users to toggle instantly between Kilometers (km) Miles (mi) during calculation to avoid manual conversion errors. Checksum Correction

: Automatically calculate and fix the checksum of the modified file to ensure the instrument cluster or ECU accepts the new data without error codes. History & VIN Tracking Benefits of Using Tachosoft Mileage Calculator

: Offer a secure "My Dumps" section where users can save their work by VIN, allowing them to revert to original files or track changes over time. Mobile-Responsive Interface

: Ensure the tool works flawlessly on tablets and smartphones, enabling technicians to perform calculations directly from the garage floor using a mobile browser. API Integration

: Provide an API for professional workshops to integrate the calculator directly into their existing diagnostic or inventory management software. Omni Calculator Comparison: Online vs. Desktop Legacy TachoSoft Desktop Optimized Online Version Requires manual downloads Real-time, automatic Accessibility Limited to one PC Any device with a browser File Handling Manual hex editing required Upload and auto-process Verification User must verify car type Auto-detection from file dump TachoSoft Mileage Calculator Software 23.1 User Manual

Why "Online Better" is the New Industry Standard

The phrase “online better” refers to a paradigm shift from desktop software to cloud-based utilities. Here is how a modern online mileage calculator outshines the legacy TachoSoft desktop version.

10. SEO Keywords (for backend or meta tags)

odometer correction, mileage calculator, Tachosoft tool, speedometer error, fuel economy adjustment, tire size compensation

6. Community & Live Support

The online platform often includes direct links to pinouts, wiring diagrams, and even community feedback. If an algorithm is wrong, it gets reported and fixed within hours, not months. Some online tiers include live chat support from experienced users and moderators.

Conclusion

In this work, we introduce Voyager, the first LLM-powered embodied lifelong learning agent, which leverages GPT-4 to explore the world continuously, develop increasingly sophisticated skills, and make new discoveries consistently without human intervention. Voyager exhibits superior performance in discovering novel items, unlocking the Minecraft tech tree, traversing diverse terrains, and applying its learned skill library to unseen tasks in a newly instantiated world. Voyager serves as a starting point to develop powerful generalist agents without tuning the model parameters.

Media Coverage

"They Plugged GPT-4 Into Minecraft—and Unearthed New Potential for AI. The bot plays the video game by tapping the text generator to pick up new skills, suggesting that the tech behind ChatGPT could automate many workplace tasks." - Will Knight, WIRED

"The Voyager project shows, however, that by pairing GPT-4’s abilities with agent software that stores sequences that work and remembers what does not, developers can achieve stunning results." - John Koetsier, Forbes

"Voyager, the GTP-4 bot that plays Minecraft autonomously and better than anyone else" - Ruetir

"This AI used GPT-4 to become an expert Minecraft player" - Devin Coldewey, TechCrunch

Coverage Index: [Atmarkit] [Career Engine] [Crast.net] [Daily Top Feeds] [Entrepreneur en Espanol] [Finance Jxyuging] [Forbes] [Forbes Argentina] [Gaming Deputy] [Gearrice] [Haberik] [Head Topics] [InfoQ] [ITmedia News] [Mark Tech Post] [Medium] [MSN] [Note] [Noticias de Hoy] [Ruetir] [Stock HK] [Tech Tribune France] [TechCrunch] [TechBeezer] [Toutiao] [US Times Post] [VN Explorer] [WIRED] [Zaker]

Team

Guanzhi Wang

Yuqi Xie

Yunfan Jiang^*

Ajay Mandlekar^*

Chaowei Xiao

Yuke Zhu

Linxi "Jim" Fan^†

Anima Anandkumar^†

* Equal Contribution † Equal Advising

BibTeX

@article{wang2023voyager,
  title   = {Voyager: An Open-Ended Embodied Agent with Large Language Models},
  author  = {Guanzhi Wang and Yuqi Xie and Yunfan Jiang and Ajay Mandlekar and Chaowei Xiao and Yuke Zhu and Linxi Fan and Anima Anandkumar},
  year    = {2023},
  journal = {arXiv preprint arXiv: Arxiv-2305.16291}
}