Active Inference as a Convex Markov Decision Process

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

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ethics.ai (22 July 2026), “Active Inference as a Convex Markov Decision Process,” evidence record 12962, https://ethics.ai/record/12962 (originally published by arXiv cs.AI).

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