220 citations · 313 across the 8 of their papers we have counts for
4 papers · 1 filter
Imitating Graph-Based Planning with Goal-Conditioned Policies
Junsu Kim, Younggyo Seo, Sungsoo Ahn +2
Recently, graph-based planning algorithms have gained much attention to solve goal-conditioned reinforcement learning (RL) tasks: they provide a sequence of subgoals to reach the t…
QTRAN++: Improved Value Transformation for Cooperative Multi-Agent Reinforcement Learning
Kyunghwan Son, Sungsoo Ahn, Roben Delos Reyes +2
QTRAN is a multi-agent reinforcement learning (MARL) algorithm capable of learning the largest class of joint-action value functions up to date. However, despite its strong theoret…
Solving Continual Combinatorial Selection via Deep Reinforcement Learning
Hyungseok Song, Hyeryung Jang, Hai H. Tran +5
We consider the Markov Decision Process (MDP) of selecting a subset of items at each step, termed the Select-MDP (S-MDP). The large state and action spaces of S-MDPs make them intr…
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…