DRAFT - Event-Governed Free Energy: A Constrained Thermodynamic Framework

The Free Energy Principle (FEP) provides a unifying variational account of inference and action, but in unconstrained form admits degenerate equilibria, including representational collapse, refusal dynamics, and internally consistent yet externally ungrounded certainty. These pathologies persist across active inference extensions because optimization is defined over latent internal states rather than directly over observable behavior and its consequences. We derive the Event-Governed Free Energy Principle (EG-FEP), a constrained free-energy formulation defined over an explicit event space, in which policies select observable actions subject to enforceable governance constraints. A normative reference distribution specifies admissible behavior, while hard law barriers impose a strict feasibility region that excludes epistemically inert or self-sealing strategies. Mandatory dissipation requirements enforce continual external contact, preventing representational closure, and a push–path waste regularizer penalizes certainty, intervention, or control expenditure not supported by productive work. We show that these constraints eliminate all trivial, solipsistic, and non-interacting minima admitted by unconstrained FEP, leaving only externally grounded, work-performing regimes. We further demonstrate that EG-FEP is not merely normative but empirically instantiated: analysis of longitudinal telemetry from governed human–AI interaction systems shows that policies minimizing the EG-FEP functional exhibit stable, adaptive, and productive behavior, while pathological regimes violate its constraints and fail to persist. EG-FEP generalizes the Free Energy Principle from belief optimization to governance optimization, providing a formal foundation for robust control, coordination, and persistence across biological, artificial, and institutional systems. This work forms part of a broader research program examining how rendering, constraint, and convergence emerge in uncertain physical, cognitive, and social systems. Research Program Invitation - https://grodriguez6.github.io/amo-collab