In this paper we present the probabilistic typed natural deduction calculus TPTND, designed to reason about and derive trustworthiness properties of probabilistic computational processes, like those underlying current AI applications. Derivability in TPTND is interpreted as the process of extracting n samples of possibly complex outputs with a certain frequency from a given categorical distribution.
authors:
Fabio Aurelio D'Asaro, Francesco Genco, Giuseppe Primiero
keywords:
Trustworthiness, Probabilistic Computations, Typed Natural Deduction
