让浏览器智能体像人一样互动式浏览，边做边问，更懂用户意图。
Interaction-Driven Browsing: A Human-in-the-Loop Conceptual Framework Informed by Human Web Browsing for Browser-Using Agents
- 智能体主动提下一步操作，用户通过反馈引导浏览方向。
- 区分探索与利用动作，灵活控制浏览广度和深度。
- 适合需要复杂决策的网页任务，如信息搜集与多步骤操作。
尽管浏览器使用智能体（BUAs）在网页任务和自动化方面展现出潜力，但大多数智能体在执行单一指令后即终止，难以支持用户复杂的、非线性的浏览行为，如目标模糊、迭代决策和情境变化。本文提出一个受人类网页浏览行为理论启发的人机协同（HITL）概念框架。该框架以迭代循环为核心：智能体主动建议下一步操作，用户通过反馈引导浏览进程。同时，框架区分探索与利用行为，使用户可调控浏览的广度与深度。由此，框架旨在降低用户的身心负担，保持传统浏览的心理模型，并帮助用户达成满意结果。我们通过假设性用例展示框架运作方式，并讨论从手动浏览到交互驱动浏览的转变。本研究贡献了一个基于理论的BUA概念框架。
原文摘要 · Abstract (English)
Although browser-using agents (BUAs) show promise for web tasks and automation, most BUAs terminate after executing a single instruction, failing to support users' complex, nonlinear browsing with ambiguous goals, iterative decision-making, and changing contexts. We present a human-in-the-loop (HITL) conceptual framework informed by theories of human web browsing behavior. The framework centers on an iterative loop in which the BUA proactively proposes next actions and the user steers the browsing process through feedback. It also distinguishes between exploration and exploitation actions, enabling users to control the breadth and depth of their browsing. Consequently, the framework aims to reduce users' physical and cognitive effort while preserving users' traditional browsing mental model and supporting users in achieving satisfactory outcomes. We illustrate how the framework operates with hypothetical use cases and discuss the shift from manual browsing to interaction-driven browsing. We contribute a theoretically informed conceptual framework for BUAs.
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