---
格式版本: 2
标题: "MEGA: Self-Evolving Agent Optimization Infrastructure via Wisdom Graph"
原文链接: "https://arxiv.org/abs/2608.10504"
发布日期: "2026-08-11"
发布时间校准状态: "found"
发布时间需复核: "否"
发布时间来源: "rule:local:strict_original_body"
发布时间证据: "**\\[v1\\]** Tue, 11 Aug 2026 05:21:16 UTC (440 KB)"
发布时间校准原因: "规则确认唯一严格发布时间，来源 local:strict_original_body"
发布时间校准置信度: "high"
发布时间候选数量: 18
发布时间严格候选数量: 6
发布时间原页读取状态: "source template page reused from URL open"
发布时间未找到原因: ""
发布时间校准时间: "2026-08-12T10:58:04+08:00"
发布时间仲裁状态: "skipped"
发布时间仲裁尝试次数: 0
发布时间仲裁耗时毫秒: 0
发现时间: "2026-08-12T10:56:49+08:00"
入库时间: "2026-08-12T02:58:04.115Z"
来源平台: "arXiv 学术论文搜索"
搜索渠道: "source_template"
搜索词: "https://arxiv.org/search/?query=Meta&searchtype=all"
匹配关键词:
  - "AI"
相关厂家:
  - "Meta"
相关专家:
  []
内容类型: "网页"
抓取工具: "Free Fetch + Defuddle"
清洗工具: "Defuddle Markdown + Defuddle/Readability 正文提取"
原始附件:
  []
AI优质: "否"
AI打分: 10
AI分档: "非优质"
AI质检状态: "不通过"
AI打分理由: "论文主题为AI agent优化基础设施，与超节点、AI Rack、机柜级AI硬件、供电散热互连等完全无关，属于算法领域，不涉及项目关注范围。"
AI质检模型: "ali-deepseek-v4-flash"
AI质检时间: "2026-08-12T10:58:16+08:00"
AI主题相关性: 0
AI来源权威性: 10
AI新颖性: 0
AI技术细节: 0
AI商业部署信号: 0
AI完整性: 0
采集批次: "2026年8月12日2点04分20秒"
采集批次ID: "20260812-020420-289"
去重键: "https://arxiv.org/abs/2608.10504"
---

## Computer Science > Artificial Intelligence

## Title:MEGA: Self-Evolving Agent Optimization Infrastructure via Wisdom Graph

Authors:[Jung Hwan Lee](https://arxiv.org/search/cs?searchtype=author&query=Lee,+J+H), [Kyu Ho Lee](https://arxiv.org/search/cs?searchtype=author&query=Lee,+K+H), [Gwang Hoon Yoo](https://arxiv.org/search/cs?searchtype=author&query=Yoo,+G+H)

[View PDF](https://arxiv.org/pdf/2608.10504)

> Abstract:As coding agents increasingly handle implementation, the central challenge shifts from building individual agents to building an infrastructure that systematically improves them. Current approaches optimize agent systems without accumulating transferable knowledge, accumulate knowledge without compositional reasoning over it, and lack a mechanism for that knowledge to self-evolve through operational evidence. MEGA (Meta Evaluation-Grounded Adaptation) addresses these gaps as a self-evolving infrastructure: each optimization cycle produces durable assets, compositional reasoning over those assets guides subsequent optimization, and operational evidence refines both the accumulated wisdom and the reasoning that governs it. Layer 1 distills reusable wisdom from agent sessions through behavioral-pattern clustering and empirical A/B validation, transforming each process into a durable asset. Layer 2 decomposes these assets into atomic PCR (Primary-Context-Resultant) units within a typed Wisdom Graph and performs deductive, abductive, and inductive reasoning to expand implicit relations; it then assembles context-specific execution plans through compositional retrieval that surfaces bridging knowledge unreachable by embedding similarity alone. Layer 3 performs multi-agent collaborative optimization over heterogeneous agent workflows (code nodes, LLM calls, and tool-using agents), attributing improvement effects to specific strategy changes through controlled evaluation that eliminates data variance. Evidence fed back from Layer 3 drives the self-evolution of both the curation strategies that govern wisdom composition and the optimization trajectories accumulated across runs. The result is an infrastructure in which optimizing an agent system and evolving the knowledge that guides optimization are one and the same process.

| Comments: |  |
| --- | --- |
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | [arXiv:2608.10504](https://arxiv.org/abs/2608.10504) \[cs.AI\] |
|  | (or [arXiv:2608.10504v1](https://arxiv.org/abs/2608.10504v1) \[cs.AI\] for this version) |
|  | [https://doi.org/10.48550/arXiv.2608.10504](https://doi.org/10.48550/arXiv.2608.10504) |

## Submission history

From: Jung Hwan Lee \[[view email](https://arxiv.org/show-email/2b62412c/2608.10504)\]  
**\[v1\]** Tue, 11 Aug 2026 05:21:16 UTC (440 KB)

[Which authors of this paper are endorsers?](https://arxiv.org/auth/show-endorsers/2608.10504) | Disable MathJax ([What is MathJax?](https://info.arxiv.org/help/mathjax.html))
