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cs.LG2025
Multi-Objective Reinforcement Learning with Max-Min Criterion: A Game-Theoretic Approach
Woohyeon Byeon, Giseung Park, Jongseong Chae +2
In this paper, we propose a provably convergent and practical framework for multi-objective reinforcement learning with max-min criterion. From a game-theoretic perspective, we ref…
cs.LG2025
Reward Dimension Reduction for Scalable Multi-Objective Reinforcement Learning
Giseung Park, Youngchul Sung
In this paper, we introduce a simple yet effective reward dimension reduction method to tackle the scalability challenges of multi-objective reinforcement learning algorithms. Whil…