Michael D. Kirchhoff

Authored papers (1)

• A tale of two densities: active inference is enactive inference2020ⓒ 225

  Ramstead, Kirchhoff, and Friston argue that generative models in active inference under the free energy principle (FEP) are control systems—not structural representations—and that this distinction has been systematically obscured by conflating active inference with brain-centered Bayesian frameworks such as predictive coding (Rao & Ballard, 1999), the Helmholtz machine (Dayan et al., 1995), and Bishop's (2006) variational machine learning. The load-bearing move is a technical one: under the FEP, generative models are entailed by the adaptive dynamics of an organism rather than encoded in physical neural states, while it is the recognition density that is embodied—parameterized by the sufficient statistics of internal Markov blanket states. The paper introduces the construct of enactive inference, a reinterpretation grounding the generative model as a normative control system in the tradition of Conant and Ross Ashby's (1970) good regulator theorem, distinguishing it sharply from the structural representationalist accounts advanced by Kiefer and Hohwy (2018, 2019) and Gładziejewski and Miłkowski (2017). Representationalists are correct that internal states encode exploitable structural similarities, but they misidentify the vehicle: those states parameterize the recognition density, not the generative model. The paper argues this implies that perception and action are inseparable moments of a single policy-selection process, that cognitive science should shift from asking how brains represent the world to how organisms enact attunement to their ecological niche, and that enactivism and the mathematical apparatus of active inference are mutually reinforcing rather than in tension.

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  ramstead_2020_two_densities.md