AetherLabsAI/RSIAgent

A training-free multi-agent framework for recursive self-improvement in new environments through broad-then-deep autonomous exploration and reusable memory.

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<img src="https://img.shields.io/badge/Companion-RSIGame-FF7A45?style=flat&logo=github&logoColor=white" News · Demos · Method · Results · Quickstart · Documentation · Citation https://github.com/user-attachments/assets/11cb3919-1073-4ba3-8bcd-37a15ec53c33 RSIAgent is a training-free framework for recursive self-improvement in new digital environments. It coordinates the Curriculum Agent, Actor Agent, and Verifier Agent to discover how an environment works, check what they learn against actual execution, and retain reusable knowledge in persistent memory. Model parameters stay fixed throughout exploration and downstream task execution. The paper's central strategy is broad-then-deep exploration: first acquire diverse experience, then investigate hard cases, hidden constraints, and boundary conditions. The resulting memory contains procedures, scripts, and failure lessons that the Actor Agent reuses for downstream task execution. https://github.com/user-attachments/assets/b939a9c2-4acb-4c30-b72e-18bab646529c [](docs/assets/framework.png) The paper's original framework figure, illustrated with a FreeCAD task. Broad experience is progressively refined into targeted memory, then frozen for reuse. Click the figure for full resolution. Figure provenance. Three agents carry out the recursive learning loop: accumulated knowledge, then decides…

AetherLabsAI/RSIAgent on GitHub A short preview, not the full document.

Read the full README ↗ · Preview checked 2026-10-30T09:36:34.487Z

Inside the original README — Document outline
  1. 📰 News & Highlights
  2. 🧭 Overview
  3. 🎬 Demos
  4. 🧩 Framework
  5. 🔄 Method
  6. 📊 Results
  7. 🧪 Benchmarks
  8. 🗂️ Repository layout
  9. ⚙️ Installation
  10. 🖥️ OSWorld
  11. 🎓 ALE
  12. 🚀 Run batches

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Documentation belongs to its respective authors. Reported project/model license: Apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

What this repository does

A training-free multi-agent framework for recursive self-improvement in new environments through broad-then-deep autonomous exploration and reusable memory.

Repository facts

Owner
AetherLabsAI
Primary language
Python
Stars
358
Forks
40
Open issues + pull requests
8
License
Apache-2.0
Archived
No
Default branch
main
Created
2026-09-13T01:48:25.000Z
Last push
2026-09-16T04:05:23.000Z

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