YOO, Woo-Sik, KIM, Jongeun, CONCHA, David Molina und LEE, Chi-Guhn, 2025. Optimizing Markov decision process state design for deep reinforcement learning manufacturing scheduling using Bayesian optimization. Journal of Computational Design & Engineering. 1 Oktober 2025. Vol. 12, no. 10, p. 154-175. DOI 10.1093/jcde/qwaf100.
Elsevier - Harvard (with titles)Yoo, W.-S., Kim, J., Concha, D.M., Lee, C.-G., 2025. Optimizing Markov decision process state design for deep reinforcement learning manufacturing scheduling using Bayesian optimization. Journal of Computational Design & Engineering 12, 154-175. https://doi.org/10.1093/jcde/qwaf100
American Psychological Association 7th editionYoo, W.-S., Kim, J., Concha, D. M., & Lee, C.-G. (2025). Optimizing Markov decision process state design for deep reinforcement learning manufacturing scheduling using Bayesian optimization. Journal of Computational Design & Engineering, 12(10), 154-175. https://doi.org/10.1093/jcde/qwaf100
Springer - Basic (author-date)Yoo W-S, Kim J, Concha DM, Lee C-G (2025) Optimizing Markov decision process state design for deep reinforcement learning manufacturing scheduling using Bayesian optimization.. Journal of Computational Design & Engineering 12:154-175. https://doi.org/10.1093/jcde/qwaf100
Juristische Zitierweise (Stüber) (Deutsch)Yoo, Woo-Sik/ Kim, Jongeun/ Concha, David Molina/ Lee, Chi-Guhn, Optimizing Markov decision process state design for deep reinforcement learning manufacturing scheduling using Bayesian optimization., Journal of Computational Design & Engineering 2025, 154-175.