no code implementations • 13 May 2020 • Han Cha, Jihong Park, Hyesung Kim, Mehdi Bennis, Seong-Lyun Kim
Traditional distributed deep reinforcement learning (RL) commonly relies on exchanging the experience replay memory (RM) of each agent.
no code implementations • 16 Aug 2019 • Jihong Park, Shiqiang Wang, Anis Elgabli, Seungeun Oh, Eunjeong Jeong, Han Cha, Hyesung Kim, Seong-Lyun Kim, Mehdi Bennis
Devices at the edge of wireless networks are the last mile data sources for machine learning (ML).
no code implementations • 15 Jul 2019 • Han Cha, Jihong Park, Hyesung Kim, Seong-Lyun Kim, Mehdi Bennis
In distributed reinforcement learning, it is common to exchange the experience memory of each agent and thereby collectively train their local models.