mlsanityData to 7 Oct 2026

MineStudio: A Streamlined Package for Minecraft AI Agent Development

arXiv 2412.18293 ↗First posted 24 Dec 2024cs.AIcited by 12

Not on the map. Why?

Abstract (arXiv)

Minecraft's complexity and diversity as an open world make it a perfect environment to test if agents can learn, adapt, and tackle a variety of unscripted tasks. However, the development and validation of novel agents in this setting continue to face significant engineering challenges. This paper presents MineStudio, an open-source software package designed to streamline the development of autonomous agents in Minecraft. MineStudio represents the first comprehensive integration of seven critical engineering components: simulator, data, model, offline pre-training, online fine-tuning, inference, and benchmark, thereby allowing users to concentrate their efforts on algorithm innovation. We provide a user-friendly API design accompanied by comprehensive documentation and tutorials. Our project is released at https://github.com/CraftJarvis/MineStudio.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 14 of its 21 references that are in the map. First posted on arXiv 24 Dec 2024.

Builds on

14 of 21 references.

References · 14

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,081
  3. 2019Transformer-XL: Attentive Language Models Beyond a Fixed-Length Contextcited by 1,830
  4. 2019Habitat: A Platform for Embodied AI Researchcited by 1,163
  5. 2017Ray: A Distributed Framework for Emerging AI Applicationscited by 516
  6. 2019Leveraging Procedural Generation to Benchmark Reinforcement Learningcited by 478
  7. 2022MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledgecited by 469
  8. 2022Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videoscited by 338
  9. 2023Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memorycited by 288
  10. 2019MineRL: A Large-Scale Dataset of Minecraft Demonstrationscited by 210
  11. 2023JARVIS-1: Open-World Multi-task Agents with Memory-Augmented Multimodal Language Modelscited by 170
  12. 2023STEVE-1: A Generative Model for Text-to-Behavior in Minecraftcited by 95
2 more
  1. 2023GROOT: Learning to Follow Instructions by Watching Gameplay Videoscited by 42
  2. 2024ROCKET-1: Mastering Open-World Interaction with Visual-Temporal Context Promptingcited by 20

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 8.

12 papers.

  1. 2025A Survey on Vision-Language-Action Models: An Action Tokenization Perspectivecited by 96
  2. 2025Infinite Mobility: Scalable High-Fidelity Synthesis of Articulated Objects via Procedural Generationcited by 17
  3. 2025ROCKET-2: Steering Visuomotor Policy via Cross-View Goal Alignmentcited by 6
  4. 2025MineAnyBuild: Benchmarking Spatial Planning for Open-world AI Agentscited by 3
  5. 2026MMG2Skill: Can Agents Distill In-the-Wild Guides into Self-Evolving Skills?cited by 2
  6. 2026OnlineWM: Causality-Aware Active Online Learning for Effective World Modelingcited by 2
  7. 2026Multi-agent Framework for Time-Sensitive Complementary Collaboration in Minecraftcited by 1
  8. 2026ActSWM: Action-Sensitive World Models for Long-Horizon Planning in Open-World Gamescited by 1
  9. 2026World2Minecraft: Occupancy-Driven Simulated Scenes Constructioncited by 0
  10. 2026Completion at the Boundary (CaB): Deployable Switching with Completion-Aware Control under Limited Calibrationcited by 0
  11. 2026GameWAM: A World Action Model for Video Gamescited by 0
  12. 2026GameHorizon Suite: Multi-Horizon Data and Evaluation in Gameplaycited by 0