Optimizing and extending the functionality of EXARL for scalable reinforcement learning

Sai Chenna (1, 2) , Katherine Cosburn (1, 3) , Uchenna Ezeobi (1, 4) , Maxim Moraru (1, 5) , Hyun Lim (1) , Julien Loiseau (1) , Jamal Mohd-Yusof (1) , Robert Pavel (1) , Vinay Ramakrishnaiah (1) , Andrew Reisner (1) , Karen Tsai (1)

1 LANL - Los Alamos National Laboratory
2 UF - University of Florida [Gainesville]
3 The University of New Mexico [Albuquerque]
4 University of Colorado [Colorado Springs]
5 URCA - Université de Reims Champagne-Ardenne

Domaines: Apprentissage [cs.LG]; Calcul parallèle, distribué et partagé [cs.DC]

Sai Chenna, Katherine Cosburn, Uchenna Ezeobi, Maxim Moraru, Hyun Lim, et al.. Optimizing and extending the functionality of EXARL for scalable reinforcement learning. SC21 - Supercomputing 2021, Nov 2021, Saint-Louis, United States. . ⟨cea-03780809⟩