让人类与AI协作规划执行任务，支持动态调整和灵活分工。
Cocoa: Co-Planning and Co-Execution with AI Agents
- 通过可交互的协作计划，动态分配任务给用户或AI
- 允许规划与执行交替进行，部分执行后可调整计划
- 基于计算笔记本设计，适合科研人员长期协作使用
随着AI代理承担越来越复杂的长期任务，需要更深入的人机协作设计。现有方法要么用于修复尚未完全自主的流程，要么机械地将规划与执行分阶段处理。通过对9位研究人员的调研，我们提出一种新设计：支持用户在协作计划中灵活分配任务责任，并可在部分执行后动态调整计划。我们构建了Cocoa系统，借鉴计算笔记本的交互方式，支持复杂研究任务。实验室测试（n=16）表明，Cocoa在保持易用性的同时提升了任务可控性；为期一周的实地部署（n=7）显示，研究人员能有效利用Cocoa完成真实研究任务。
原文摘要 · Abstract (English)
As AI agents take on increasingly long-running tasks involving sophisticated planning and execution, there is a corresponding need for novel interaction designs that enable deeper human-agent collaboration. However, most prior works leverage human interaction to fix "autonomous" workflows that have yet to become fully autonomous or rigidly treat planning and execution as separate stages. Based on a formative study with 9 researchers using AI to support their work, we propose a design that affords greater flexibility in collaboration, so that users can 1) delegate agency to the user or agent via a collaborative plan where individual steps can be assigned; and 2) interleave planning and execution so that plans can adjust after partial execution. We introduce Cocoa, a system that takes design inspiration from computational notebooks to support complex research tasks. A lab study (n=16) found that Cocoa enabled steerability without sacrificing ease-of-use, and a week-long field deployment (n=7) showed how researchers collaborated with Cocoa to accomplish real-world tasks.
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