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English(EN) Governed Self-Evolution for Autonomous Investing: A Multi-Agent LLM System with an Invariant Core

新LLM系统“Steward”通过自我进化增强自主投资能力

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了Steward，一个专为自主投资设计的新型多智能体LLM系统。该系统包含九个专业智能体，包括分析师、投资组合经理和风险经理，共同做出投资决策。Steward采用七层共享内存来情境化决策，并包含一个自我改进机制，该机制会审查交易并提出可逆的学习。该架构旨在通过围绕一套不可被自我编辑修改的规则和提示的不变核心来运行，从而提高性能和安全性。 AI

影响 该系统有望通过提高其安全性和适应性，来推进LLM在高风险金融决策中的应用。

排序理由 该集群描述了一篇研究论文，其中详细介绍了一个使用LLM进行自主投资的新型系统。

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新LLM系统“Steward”通过自我进化增强自主投资能力

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该集群描述了一篇研究论文，其中详细介绍了一个使用LLM进行自主投资的新型系统。
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报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Yebo Feng, Jingyang Dai, Liangrui Pan, Nelson Lau, Jiahua Xu, Yang Liu ·

    Governed Self-Evolution for Autonomous Investing: A Multi-Agent LLM System with an Invariant Core

    arXiv:2610.30557v1 Announce Type: cross Abstract: LLM agents that act on live Web data must combine heterogeneous evidence, remember what they have done and improve from outcomes without weakening their own safeguards. We study this problem in autonomous investing, where every ac…

  2. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Yang Liu ·

    Governed Self-Evolution for Autonomous Investing: A Multi-Agent LLM System with an Invariant Core

    LLM agents that act on live Web data must combine heterogeneous evidence, remember what they have done and improve from outcomes without weakening their own safeguards. We study this problem in autonomous investing, where every action is irreversible and based on untrusted Web co…

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