Learning and total evidence with imprecise probabilities (2022)
Gong, Ruobin 
; Kadane, Joseph B. ; Schervish, Mark J. ; Seidenfeld, Teddy ; Stern, Rafael Bassi
Fonte: International Journal of Approximate Reasoning. Unidade: IME
Assuntos: INTELIGÊNCIA ARTIFICIAL, ENGENHARIA DE SOFTWARE
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ABNT
GONG, Ruobin et al. Learning and total evidence with imprecise probabilities. International Journal of Approximate Reasoning, v. 151, p. 21-32, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.ijar.2022.08.016. Acesso em: 09 nov. 2025.APA
Gong, R., Kadane, J. B., Schervish, M. J., Seidenfeld, T., & Stern, R. B. (2022). Learning and total evidence with imprecise probabilities. International Journal of Approximate Reasoning, 151, 21-32. doi:10.1016/j.ijar.2022.08.016NLM
Gong R, Kadane JB, Schervish MJ, Seidenfeld T, Stern RB. Learning and total evidence with imprecise probabilities [Internet]. International Journal of Approximate Reasoning. 2022 ; 151 21-32.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1016/j.ijar.2022.08.016Vancouver
Gong R, Kadane JB, Schervish MJ, Seidenfeld T, Stern RB. Learning and total evidence with imprecise probabilities [Internet]. International Journal of Approximate Reasoning. 2022 ; 151 21-32.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1016/j.ijar.2022.08.016
