{
  "id": 12962,
  "url": "https://arxiv.org/abs/2607.20152v1",
  "title": "Active Inference as a Convex Markov Decision Process",
  "summary": "Active Inference (AIF) frames adaptive behavior as the minimization of expected free energy (EFE), combining epistemic and pragmatic objectives within a single variational principle. We frame AIF as policy optimization and show that, for closed-loop control policies, EFE minimization can be formulated as a convex Markov decision process (MDP). In this formulation, the pragmatic terms are linear in the predictive state marginals and therefore equivalent to reward maximization in a latent MDP, whi",
  "authors": "Nikola Milosevic, Nicolás Hinrichs, Nico Scherf",
  "category": "research",
  "topics": "regulation,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-22T13:52:40.000Z",
  "fetched_at": "2026-07-23T05:10:49.458Z",
  "source_slug": "x-arxiv-cs-ai",
  "source_name": "arXiv cs.AI",
  "source_homepage": "https://arxiv.org/list/cs.AI/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/12962",
  "original_url": "https://arxiv.org/abs/2607.20152v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}