Reinforcement Learning for Scalable and Trustworthy Intelligent Systems

ArXi:2605.08378v1 Announce Type: cross Reinforcement learning has become a powerful paradigm for improving the capability of intelligent systems, but its practical deployment faces two central challenges. First, reinforcement learning must scale efficiently in distributed environments where communication bandwidth is limited and computation is heterogeneous across agents. Second, as reinforcement learning is increasingly used in post-