OS-Copilot: Towards Generalist Computer Agents with Self-Improvement
Source
- Person key:
ysymyth - Source kind:
paper - Canonical URL: https://arxiv.org/abs/2402.07456
- License:
NOASSERTION - Public handling:
public-metadata-summary-hash-link-only - Semantic hash:
23e237eb2b9a97e8f54beff8876d1c3bb6794527e69a5ac97e3199d2fca82a0a - First seen: 2026-05-16
- Last changed: 2026-05-16
- Identity guard: Do not confuse with yao-shunyu-alfred, the physics-to-AI researcher at alfredyao.github.io.
Classification
- Category: Language agents / agent architectures
- Topic hub: shunyu-yao-public-corpora
- Project taxonomy: shunyu-yao-project-taxonomy
- Paper map: shunyu-yao-paper-map
Summary
Autonomous interaction with the computer has been a longstanding challenge with great potential, and the recent proliferation of large language models (LLMs) has markedly accelerated progress in building digital agents. However, most of these agents are designed to interact with a narrow domain, such as a specific software or website. This narrow focus constrains their applicability for general computer tasks. To this end, we introduce OS-Copilot, a framework to build generalist agents capable of interfacing with c…
What This Teaches
How language models become agents through reasoning, acting, memory, tools, and interface design.
Related
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