DuoCook: An Overcooked-Inspired Benchmark for Visual Planning and Coordination· DuoCook: 双人协作烹饪任务的基准测试
Coordinating two players in a cooking task requires a vision-language agent to track changing scene states, sequence recipe steps, and allocate shared resources under a time budget. We introduce an Overcooked-inspired benchmark for evaluating these capabilities in Unreal Engine environments constructed using coding agents. A single vision-language model controls both players from top-down visual observations, selecting high-level actions while the engine executes navigation. The benchmark contains 20 maps in five categories. These categories support evaluation of centralized coordination under equipment contention, changing terrain, and handoff dependencies. A prop legend and pot ingredient-count indicators provide explicit visual cues, while grid-based destinations support spatial groundi
双人协作烹饪任务的视觉规划与协同新基准
- 核心方法
- 引入了一个基于Unreal Engine的Overcooked启发式基准测试,该测试环境由代码代理构建,使用单个视觉语言模型从俯视角度观察场景并选择高级别动作,同时考虑设备争用、地形变化和交接依赖等多方面因素
- 适合谁读
- 研究者 / 工程师
- 要解决的问题
- 多玩家在烹饪任务中的高效视觉规划和协同动作执行
- 关键实验
- 实验评估了不同地图上的模型性能,特别是在设备争用、地形变化和手递依赖等场景下的表现
- 主要贡献
- 提供了一个新的基准测试集,包含20个不同类别的地图,用于评估视觉语言代理在共享资源和时间限制下的规划与协调能力
- 意义与局限
- 该基准测试有助于推动视觉规划和多代理协作研究的发展,但也可能受到环境复杂度和模型泛化能力的限制