Source: PMLR: Proceedings of Machine Learning Research. Conference titles: International Symposium on Imprecise Probability: Theories and Applications - ISIPTA. Unidades: IME, EP
Subjects: PROCESSOS DE MARKOV, PROGRAMAÇÃO LÓGICA, MODELOS PARA PROCESSOS ESTOCÁSTICOS
ABNT
BUENO, Thiago Pereira et al. Modeling Markov decision processes with imprecise probabilities using probabilistic logic programming. PMLR: Proceedings of Machine Learning Research. Brookline: Instituto de Matemática e Estatística, Universidade de São Paulo. Disponível em: http://proceedings.mlr.press/v62/bueno17a.html. Acesso em: 19 nov. 2024. , 2017APA
Bueno, T. P., Mauá, D. D., Barros, L. N. de, & Cozman, F. G. (2017). Modeling Markov decision processes with imprecise probabilities using probabilistic logic programming. PMLR: Proceedings of Machine Learning Research. Brookline: Instituto de Matemática e Estatística, Universidade de São Paulo. Recuperado de http://proceedings.mlr.press/v62/bueno17a.htmlNLM
Bueno TP, Mauá DD, Barros LN de, Cozman FG. Modeling Markov decision processes with imprecise probabilities using probabilistic logic programming [Internet]. PMLR: Proceedings of Machine Learning Research. 2017 ;( 62): 49-60.[citado 2024 nov. 19 ] Available from: http://proceedings.mlr.press/v62/bueno17a.htmlVancouver
Bueno TP, Mauá DD, Barros LN de, Cozman FG. Modeling Markov decision processes with imprecise probabilities using probabilistic logic programming [Internet]. PMLR: Proceedings of Machine Learning Research. 2017 ;( 62): 49-60.[citado 2024 nov. 19 ] Available from: http://proceedings.mlr.press/v62/bueno17a.html