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What is Learnable in Valiant's Theory of the Learnable? 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Compositional Active Inference I: Bayesian Lenses. Statistical Games
Toby St. Clere Smithe · 2021-09-10 · via math.ST updates on arXiv.org

We introduce the concepts of Bayesian lens, characterizing the bidirectional structure of exact Bayesian inference, and statistical game, formalizing the optimization objectives of approximate inference problems. We prove that Bayesian inversions compose according to the compositional lens pattern, and exemplify statistical games with a number of classic statistical concepts, from maximum likelihood estimation to generalized variational Bayesian methods. This paper is the first in a series laying the foundations for a compositional account of the theory of active inference, and we therefore pay particular attention to statistical games with a free-energy objective.

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