{
  "id": 7105,
  "url": "https://arxiv.org/abs/2603.16586v1",
  "title": "Runtime Governance for AI Agents: Policies on Paths",
  "summary": "AI agents -- systems that plan, reason, and act using large language models -- produce non-deterministic, path-dependent behavior that cannot be fully governed at design time, where with governed we mean striking the right balance between as high as possible successful task completion rate and the legal, data-breach, reputational and other costs associated with running agents. We argue that the execution path is the central object for effective runtime governance and formalize compliance policie",
  "authors": "Maurits Kaptein, Vassilis-Javed Khan, Andriy Podstavnychy",
  "category": "research",
  "topics": "regulation,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-17T14:35:52.000Z",
  "fetched_at": "2026-07-14T16:32:59.165Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7105",
  "original_url": "https://arxiv.org/abs/2603.16586v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}