{
  "id": 1619439,
  "title": "ClawGym II: Exploring Black-Box RL on Agent Harness",
  "url": "https://urgent.news/2026/08/17/clawgym-ii-exploring-black-box-rl-on-agent-harness",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-17T16:53:03.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2608.16798v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Agent harnesses have substantially improved performance on long-horizon tasks by coordinating agent interactions with the environment. However, reinforcement learning through complex harnesses remains largely unexplored, as scaling such training to long-horizon agent tasks introduces fundamental challenges. In this work, we present a unified black-box RL framework for stable and scalable…",
  "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."
}