Active inference of extended finite state models of software systems (2023)
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
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: 30 ago. 2024. , 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 2024 ago. 30 ] 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 2024 ago. 30 ] Available from: https://proceedings.mlr.press/v217/groz23a.html