Bayesian Convergence for Computably Bounded Agents.

In this article, we pursue two goals. First, we argue that computable probability theory offers a fitting framework for modeling the credences of computably bounded—and, thus, more realistic—Bayesian reasoners. Second, we develop a Bayesian perspective on algorithmic randomness: a branch of computab...

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Detalles Bibliográficos

Publicado en:	Philosophy & Phenomenological Research Vol. 112; no. 1; pp. 307 - 325
Autores principales:	Huttegger, Simon M., Walsh, Sean, Zaffora Blando, Francesca
Formato:	Artículo
Publicado:	Wiley-Blackwell Jan2026
Materias:	Bayesian analysis Probability theory Algorithms Theory of knowledge Truth
Acceso en línea:	Ver este registro en EBSCOhost