Agent S: An Open Agentic Framework That Uses Computers like a Human

Abstract

We present Agent S, an open agentic framework that enables autonomous interaction with computers through Graphical User Interface (GUI), aimed at transforming human-computer interaction by automating complex, multi-step tasks. Agent S addresses three key challenges in automating computer tasks: acquiring domain-specific knowledge, planning over long task horizons, and handling dynamic, non-uniform interfaces. To this end, Agent S introduces experience-augmented hierarchical planning, which learns from external knowledge search and internal experience retrieval at multiple levels, facilitating efficient task planning and subtask execution. In addition, it employs an Agent-Computer Interface (ACI) to better elicit the reasoning and control capabilities of GUI agents based on Multimodal Large Language Models (MLLMs). Evaluation on the OSWorld benchmark shows that Agent S outperforms the baseline by 9.37% on success rate (an 83.6% relative improvement) and achieves a new state-of-the-art. Comprehensive analysis highlights the effectiveness of individual components and provides insights for future improvements. Furthermore, Agent S demonstrates broad generalizability to different operating systems on a newly-released WindowsAgentArena benchmark. Code will be made publicly available.

Cite

Text

Agashe et al. "Agent S: An Open Agentic Framework That Uses Computers like a Human." ICLR 2025 Workshops: AgenticAI, 2025.

Markdown

[Agashe et al. "Agent S: An Open Agentic Framework That Uses Computers like a Human." ICLR 2025 Workshops: AgenticAI, 2025.](https://mlanthology.org/iclrw/2025/agashe2025iclrw-agent/)

BibTeX

@inproceedings{agashe2025iclrw-agent,
  title     = {{Agent S: An Open Agentic Framework That Uses Computers like a Human}},
  author    = {Agashe, Saaket and Han, Jiuzhou and Gan, Shuyu and Yang, Jiachen and Li, Ang and Wang, Xin Eric},
  booktitle = {ICLR 2025 Workshops: AgenticAI},
  year      = {2025},
  url       = {https://mlanthology.org/iclrw/2025/agashe2025iclrw-agent/}
}