EVAGE：基于多智能体框架的自主MEV生成与适应

中文摘要 AI 辅助

最大可提取价值（MEV）已成为区块链生态系统中的一股重要经济力量，然而其捕获主要由经验丰富的团队主导，且策略设计和实施均依赖人工专家工作，这在异构协议和链上难以规模化扩展。我们提出了EVAGE，这是首个用于端到端MEV策略生成与适应的全自主多智能体框架。配备三种专用操作模式，它能够自动发现新型MEV变体，在不同协议间适应执行逻辑，并在链之间（包括Layer-1和Layer-2网络）移植策略。为避免MEV关键执行路径上的推理延迟，EVAGE离线生成和优化MEV机器人代码，而非直接进行实时决策。在编排器智能体的协调下，三个专用子智能体通过闭环诊断共同实现和修复完整的MEV机器人工作流程，消除人工干预，同时生成经过验证且确定性的概念验证实现。我们在以太坊、Base和BNB智能链（BSC）上对EVAGE进行了评估，每个链评估超过150万区块。在以太坊上，EVAGE发现了五种新型MEV策略变体，利润提升1.02倍至15.97倍。它还将11种MEV策略从CPMM成功适应到CLMM和Balancer V2，并将策略从以太坊移植到Base和BSC，所有操作消耗的LLM代币成本低于60美元。

英文摘要

Maximal Extractable Value (MEV) has evolved into a major economic force in blockchain ecosystems, yet its capture is dominated by experienced teams, and both strategy design and implementation rely on manual expert work that scales poorly across heterogeneous protocols and chains. We present EVAGE, the first fully autonomous multi-agent framework for end-to-end MEV strategy generation and adaptation. Equipped with three specialized operation modes, it automatically discovers novel MEV variants, adapts execution logic across disparate protocols, and ports strategies between chains, including Layer-1 and Layer-2 networks. To avoid inference latency on the critical MEV execution path, EVAGE generates and refines MEV bot code offline rather than making real-time decisions directly. Under the coordination of an orchestrator agent, three specialized subagents collectively implement and repair the full MEV bot workflow via closed-loop diagnostics, eliminating human intervention while producing validated and deterministic Proof-of-Concept implementations. We evaluate EVAGE on over 1.5M blocks from each of Ethereum, Base, and BNB Smart Chain (BSC). On Ethereum, EVAGE uncovers five novel MEV strategy variants, yielding a profit increase of 1.02$\times$ to 15.97$\times$. It also successfully adapts 11 MEV strategies from CPMM to both CLMM and Balancer V2 and ports strategies from Ethereum to Base and BSC, all with less than 60 dollars in LLM token costs.

发表机构

• City University of Hong Kong（香港城市大学）
• Stony Brook University（石溪大学）
• Tsinghua University（清华大学）
• Shanghai Tech University（上海科技大学）

机构由 AI 辅助整理，请以论文原文为准。