{
  "id": 6682522,
  "title": "MAPLE: Memory-Augmented Planning with Language and Evolution",
  "url": "https://urgent.news/2026/09/10/maple-memory-augmented-planning-with-language-and-evolution",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-10T14:44:50.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.11636v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "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 established optimization tools can execute. This progress makes optimization more accessible, but real-world operations are dynamic: changing demand, resources, and…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}