Summary of Teamcraft: a Benchmark For Multi-modal Multi-agent Systems in Minecraft, by Qian Long et al.
TeamCraft: A Benchmark for Multi-Modal Multi-Agent Systems in Minecraft
by Qian Long, Zhi Li, Ran Gong, Ying Nian Wu, Demetri Terzopoulos, Xiaofeng Gao
First submitted to arxiv on: 6 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV); Multiagent Systems (cs.MA)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed paper presents a multi-modal, multi-agent benchmark called TeamCraft for evaluating the performance of generalizable collaborative agents in visually-rich environments. This benchmark is built on top of the open-world video game Minecraft and features 55,000 task variants specified by multi-modal prompts, procedurally-generated expert demonstrations for imitation learning, and carefully designed protocols to evaluate model generalization capabilities. The authors also perform extensive analyses to better understand the limitations and strengths of existing approaches. The results indicate that existing models continue to face significant challenges in generalizing to novel goals, scenes, and unseen numbers of agents. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper introduces a new benchmark called TeamCraft that helps robots work together more effectively. It’s like a big game where machines can practice collaborating with each other. The team made 55,000 different tasks for the agents to learn from and used a popular video game called Minecraft as the foundation. They tested how well the existing models worked on this new platform and found that they still struggle to adapt to new situations. This shows that we need more research in this area to help machines work together better. |
Keywords
» Artificial intelligence » Generalization » Multi modal
