6 citations · 13 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 1 cited
Quantile Constrained Reinforcement Learning: A Reinforcement Learning Framework Constraining Outage Probability
Whiyoung Jung, Myungsik Cho, Jongeui Park +1
Constrained reinforcement learning (RL) is an area of RL whose objective is to find an optimal policy that maximizes expected cumulative return while satisfying a given constraint.…
cs.MA2020★ 6 cited
A Maximum Mutual Information Framework for Multi-Agent Reinforcement Learning
Woojun Kim, Whiyoung Jung, Myungsik Cho +1
In this paper, we propose a maximum mutual information (MMI) framework for multi-agent reinforcement learning (MARL) to enable multiple agents to learn coordinated behaviors by reg…
cs.LG2019★ 6 cited
Message-Dropout: An Efficient Training Method for Multi-Agent Deep Reinforcement Learning
Woojun Kim, Myungsik Cho, Youngchul Sung
In this paper, we propose a new learning technique named message-dropout to improve the performance for multi-agent deep reinforcement learning under two application scenarios: 1)…