Samuel Blad

Samuel Blad

PhD Student

AASS Research Center
School of Science and Technology
Örebro University
70182 Örebro, Sweden
Room: T2215
Phone: No Phone Number Available
Email: samuel.blad@oru.se


Publications

[1] S. Blad, M. Längkvist, F. Klügl and A. Loutfi. Empirical analysis of the convergence of Double DQN in relation to reward sparsity. In 21st IEEE International Conference on Machine Learning and Applications. ICMLA 2022 : Proceedings, pages 591-596, 2022BibTeX | DiVA ]