Search Results for author: Han Cha

Found 3 papers, 0 papers with code

Proxy Experience Replay: Federated Distillation for Distributed Reinforcement Learning

no code implementations13 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.

Clustering Data Augmentation +3

Federated Reinforcement Distillation with Proxy Experience Memory

no code implementations15 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.

Privacy Preserving reinforcement-learning +1

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