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    autonomous agentsweb environmentevaluationUI automation

    WebArena: A Realistic Web Environment for Building Autonomous Agents

    Jason WeiIzhak ShafranYonghui WuDian YuNan DuKarthik NarasimhanShunyu Yao
    📅 2023🏛 arXiv preprint arXiv:2307.13854, presented at NeurIPS 2023
    Problem

    This paper introduces a realistic web environment for evaluating autonomous agents, including live sites and real-world tasks, to measure progress in this domain.

    Method

    WebArena provides four functional websites (e.g., online shopping, forum, project management) and a set of 812 interactive tasks that agents must perform using screen observation and actions (click, type).

    Finding

    Results show that LLM-based agents (like GPT-4) can successfully complete about 40% of tasks, which is a significant achievement, but still far from human performance (~90%).

    Limitations

    The environment is web-focused and not designed for desktop applications like Photoshop; tasks are relatively simple and do not capture the full complexity of real-world environments.

    Practical application

    WebArena serves as a standard benchmark for developing computer-use agents. In the software agent project, ideas from this paper (screen component recognition, action planning) can be applied to interact with Photoshop, though the environment differs.

    📇 Summary flashcard — 13 analytical fields for this paper

    خلاصه

    WebArena provides a realistic testbed for autonomous web agents, showing that current LLM-based agents achieve about 40% success on real-world tasks.

    نمای سریع

    A benchmark environment for web agents.

    یافته‌های کلیدی

    Results show that LLM-based agents (like GPT-4) can successfully complete about 40% of tasks, which is a significant achievement, but still far from human performance (~90%).

    هدف

    To create a realistic evaluation benchmark to advance autonomous agent research.

    روش

    WebArena provides four functional websites (e.g., online shopping, forum, project management) and a set of 812 interactive tasks that agents must perform using screen observation and actions (click, type).

    نتایج

    LLM agents achieved 40% success, a good start but still below human performance.

    نتیجه‌گیری

    Much work remains in reasoning, visual understanding, and planning to achieve truly autonomous agents.

    مفاهیم کلیدی

    autonomous agents، web environment، evaluation، UI automation

    مطالعه‌ی بیشتر

    https://arxiv.org/abs/2307.13854

    تحلیل

    This paper has been influential as one of the first comprehensive benchmarks for web agents, shaping research directions.

    محدودیت‌ها

    The environment is web-focused and not designed for desktop applications like Photoshop; tasks are relatively simple and do not capture the full complexity of real-world environments.

    کارهای آینده

    The authors emphasized developing more complex environments, improving screen interaction, and integrating with external tools.

    کاربرد عملی

    WebArena serves as a standard benchmark for developing computer-use agents. In the software agent project, ideas from this paper (screen component recognition, action planning) can be applied to interact with Photoshop, though the environment differs.

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