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Darwin Gödel Machine

#28 in Agenten-Frameworks

Sakana Ai · 3× · tolest 30. Juni 2026

32
Momentum

The Darwin Gödel Machine (DGM) is a research system for self-improving Coding Agents developed by Sakana AI in collaboration with the University of British Columbia and the Vector Institute. An Agent iteratively modifies its own Python source code and empirically validates each change against Coding Benchmarks such as SWE-bench and Polyglot, rather than formally proving improvements as in the theoretical Gödel Machine concept. The system maintains a growing archive of different Agent variants, from which new, improved descendants are generated through open exploration. The complete code is Open Source and available on GitHub; all self-modifications and evaluations run in sandboxed environments under human supervision.

Momentum-Verloop
11.07.09.10.

Features

Autonomie-GradHoch: Agent modifiziert eigenständig seinen Code, unter menschlicher Aufsicht in Sandbox mit begrenztem Web-Zugriff
LizenzCode: Apache License 2.0 (GitHub); Paper: CC BY 4.0 (arXiv)
ModalitätenCode/Text (Coding-Agent auf Basis eines eingefrorenen Foundation Models)
PlattformPython-Codebasis, lokal/GCP-VM ausführbar, Sandbox-Docker-Umgebung
Release-Datum29. Mai 2025 (arXiv-Preprint & Sakana-AI-Blog-Launch)
Tool-/MCP-IntegrationenWerkzeugnutzung wie Bash-Kommandos und Dateibearbeitung; selbst entwickelte Tools (Patch-Validierung, Datei-Viewer, Editier-Werkzeuge)

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