Active inference of extended finite state models of software systems (2023)
Groz, Roland 
; Oriat, Catherine ; Vega, Germán ; Simão, Adenilso da Silva ; Foster, Michael; Walkinshaw, Neil
Fonte: Proceedings of Machine Learning Research - PMLR. Nome do evento: International Conference on Grammatical Inference - ICGI. Unidade: ICMC
Assuntos: APRENDIZAGEM, PROGRAMAÇÃO GENÉTICA, INFERÊNCIA, ENGENHARIA DE SOFTWARE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GROZ, Roland et al. Active inference of extended finite state models of software systems. Proceedings of Machine Learning Research - PMLR. Brookline: Microtome Publishing. Disponível em: https://proceedings.mlr.press/v217/groz23a.html. Acesso em: 15 nov. 2025. , 2023APA
Groz, R., Oriat, C., Vega, G., Simão, A. da S., Foster, M., & Walkinshaw, N. (2023). Active inference of extended finite state models of software systems. Proceedings of Machine Learning Research - PMLR. Brookline: Microtome Publishing. Recuperado de https://proceedings.mlr.press/v217/groz23a.htmlNLM
Groz R, Oriat C, Vega G, Simão A da S, Foster M, Walkinshaw N. Active inference of extended finite state models of software systems [Internet]. Proceedings of Machine Learning Research - PMLR. 2023 ; 217 265-269.[citado 2025 nov. 15 ] Available from: https://proceedings.mlr.press/v217/groz23a.htmlVancouver
Groz R, Oriat C, Vega G, Simão A da S, Foster M, Walkinshaw N. Active inference of extended finite state models of software systems [Internet]. Proceedings of Machine Learning Research - PMLR. 2023 ; 217 265-269.[citado 2025 nov. 15 ] Available from: https://proceedings.mlr.press/v217/groz23a.html
