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| Main Author: | |
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| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2026
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| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.20098019 |
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Table of Contents:
- We present LocalKin, a self-evolving multi-agent swarm architecture capable of autonomously auditing, repairing, and verifying its own constituent agents without human intervention. The system runs 78 specialized agents on a single consumer machine (16GB Mac Mini) with a total memory footprint of 960MB - approximately 12.5MB per agent - compared to 200MB or more per agent in Python-based frameworks such as AutoGen and CrewAI. The core contribution is a fully autonomous improvement loop consisting of four stages: quality audit, feedback synthesis, targeted repair, and verification. Over a continuous 5-day autonomous deployment, the system completed more than 30 improvement cycles, autonomously modified 68 agent configuration files, and discovered, evaluated, and integrated techniques from 6 research papers found on arXiv and HuggingFace - all with zero human intervention.<br><br><strong>Note (2026-05-09):</strong> This version bundles English + 中文 in a single PDF (English first, then Chinese), generated directly from the canonical Markdown source files.