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cs.LG2026
Bounded Ratio Reinforcement Learning
Yunke Ao, Le Chen, Bruce D. Lee +5
Proximal Policy Optimization (PPO) has become the predominant algorithm for on-policy reinforcement learning due to its scalability and empirical robustness across domains. However…
cs.LG2025
Efficient Reinforcement Learning by Guiding World Models with Non-Curated Data
Yi Zhao, Aidan Scannell, Wenshuai Zhao +7
Leveraging offline data is a promising way to improve the sample efficiency of online reinforcement learning (RL). This paper expands the pool of usable data for offline-to-online…
cs.LG2024★ 1 cited
Identifying Policy Gradient Subspaces
Jan Schneider, Pierre Schumacher, Simon Guist +4
Policy gradient methods hold great potential for solving complex continuous control tasks. Still, their training efficiency can be improved by exploiting structure within the optim…