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English(EN) MAPLE: Memory-Augmented Planning with Language and Evolution

MAPLE 代理利用語言和演化來解決動態優化問題

研究人員開發了 MAPLE,這是一種新穎的代理,旨在通過連續的自然語言請求來管理和更新優化問題。該系統將基於語言的問題構建與數學規劃和演化搜索相結合,使其能夠保留先前的優化程序、已接受的計劃和候選解決方案以供將來迭代。MAPLE 在新的 NLDO 基準測試上進行了評估,該基準測試包含 15 個軌跡和 180 次更新,涵蓋調度、資源放置等各個領域。該代理表現強勁,在線標量質量達到 0.951,帕累托超體積比達到 0.875,同時還表明維護可執行狀態可以提高更新的有效性並保留搜索信息。 AI

影响 這項研究可以通過實現自然語言交互和動態適應,使領域從業者更容易解決複雜的優化問題。

排序理由 該項目描述了一篇詳細介紹用於優化問題的新穎代理的研究論文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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MAPLE 代理利用語言和演化來解決動態優化問題

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該項目描述了一篇詳細介紹用於優化問題的新穎代理的研究論文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Kesheng Chen, Yamin Hu, Wenjian Luo ·

    MAPLE:基于语言和演化的记忆增强规划

    arXiv:2609.11636v1 Announce Type: new Abstract: Domain practitioners understand their business constraints but may lack operations-research expertise or dedicated support. LLM-based optimization agents translate natural-language requirements into models or solver programs that es…