A Formal Framework for Knowledge Acquisition: Going beyond Machine Learning

Philosophers frequently define knowledge as justified, true belief. We built a mathematical framework that makes it possible to define learning (increasing number of true beliefs) and knowledge of an agent in precise ways, by phrasing belief in terms of epistemic probabilities, defined from Bayes’ r...

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Detalles Bibliográficos
Autores principales: Hössjer, Ola, Díaz-Pachón, Daniel Andrés, Rao, J. Sunil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9601974/
https://www.ncbi.nlm.nih.gov/pubmed/37420489
http://dx.doi.org/10.3390/e24101469

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9601974/
https://www.ncbi.nlm.nih.gov/pubmed/37420489
http://dx.doi.org/10.3390/e24101469

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