{
  "id": 18695,
  "url": "https://arxiv.org/abs/2608.10897v1",
  "title": "Partially Observable Learning for Multi-Platform Dispatch Optimization",
  "summary": "Instant delivery platforms have become a critical component of urban logistics, increasingly relying on crowdsourced couriers to fulfill highly dynamic orders. In real-world systems, couriers are not exclusive to a single platform and may concurrently serve multiple platforms, while each platform can only observe its own orders and couriers' interactions due to privacy and operational constraints. This results in a multi-platform dispatch environment with inherent partial observability. However,",
  "authors": "Fengming Yao, Man Luo",
  "category": "research",
  "topics": "privacy-surveillance,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-11T13:20:12.000Z",
  "fetched_at": "2026-08-12T05:10:43.828Z",
  "source_slug": "arxiv-cslg",
  "source_name": "arXiv cs.LG",
  "source_homepage": "https://arxiv.org/list/cs.LG/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/18695",
  "original_url": "https://arxiv.org/abs/2608.10897v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}