{
  "id": 7446890,
  "title": "Robust and Efficient Communication for Multi-Agent Learning",
  "url": "https://urgent.news/2026/09/14/robust-and-efficient-communication-for-multi-agent-learning",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-14T10:44:11.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.15361v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Effective communication is a cornerstone of distributed intelligence in Multi-Agent Reinforcement Learning (MARL), yet ensuring that generated messages are both informative and robust to physical constraints remains a significant challenge. This paper introduces Multi-Agent Regularized Communication (MARC), a novel framework inspired by information-theoretic principles of conditional mutual…",
  "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."
}