The Causally Emergent Alignment Hypothesis: Causal Emergence Aligns with and Predicts Final Reward in Reinforcement Learning Agents

{
  "doi": "10.48550/arxiv.2605.06746",
  "pdf": "https://arxiv.org/pdf/2605.06746",
  "url": "https://arxiv.org/abs/2605.06746",
  "tags": [
    "causal-emergence",
    "reinforcement-learning",
    "PhiID",
    "representation-dynamics",
    "agent-learning",
    "bio-AI-bridge",
    "levin"
  ],
  "year": 2026,
  "saved": "2026-05-14",
  "title": "The Causally Emergent Alignment Hypothesis: Causal Emergence Aligns with and Predicts Final Reward in Reinforcement Learning Agents",
  "venue": "arXiv preprint",
  "status": "full-text-saved",
  "authors": [
    "Federico Pigozzi",
    "Michael Levin"
  ],
  "arxiv_id": 2605.06746,
  "published": "2026-05-07",
  "categories": "cs.NE",
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