{
  "id": 3875,
  "url": "https://arxiv.org/abs/2606.07552v2",
  "title": "Symbolic Reasoning Frameworks Trigger Memory-Mediated Ecosystem Dynamics in Multi-Agent LLM Systems",
  "summary": "Large language models exhibit a risk-averse \"turtle\" bias as strategic agents. We show that injecting a symbolic reasoning framework as a per-round reflective prompt into one agent acts as a small perturbation whose consequences are not per-decision but emergent: the agent's risk posture is unchanged in isolation, yet over a campaign of accumulating memory and multi-agent interaction the conditions settle into distinct, condition-associated winner ecosystems. In a 7-player Warring States Diploma",
  "authors": "Augustin Chan",
  "category": "research",
  "topics": "bias-fairness,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-22T08:24:14.000Z",
  "fetched_at": "2026-07-14T16:30:36.739Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/3875",
  "original_url": "https://arxiv.org/abs/2606.07552v2",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}