220 citations · 281 across the 3 of their papers we have counts for
3 papers
Curiosity-Driven Multi-Agent Exploration with Mixed Objectives
Roben Delos Reyes, Kyunghwan Son, Jinhwan Jung +2
Intrinsic rewards have been increasingly used to mitigate the sparse reward problem in single-agent reinforcement learning. These intrinsic rewards encourage the agent to look for…
QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
Kyunghwan Son, Daewoo Kim, Wan Ju Kang +2
We explore value-based solutions for multi-agent reinforcement learning (MARL) tasks in the centralized training with decentralized execution (CTDE) regime popularized recently. Ho…
Learning to Schedule Communication in Multi-agent Reinforcement Learning
Daewoo Kim, Sangwoo Moon, David Hostallero +4
Many real-world reinforcement learning tasks require multiple agents to make sequential decisions under the agents' interaction, where well-coordinated actions among the agents are…