most citedLearn A Flexible Exploration Model for Parameterized Action Markov Decision Processes

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cs.LG2025

Controllable Flow Matching for Online Reinforcement Learning

Bin Wang, Boxiang Tao, Haifeng Jing +2

Model-based reinforcement learning (MBRL) typically relies on modeling environment dynamics for data efficiency. However, due to the accumulation of model errors over long-horizon…

cs.LG2025★ 1 cited

Learn A Flexible Exploration Model for Parameterized Action Markov Decision Processes

Zijian Wang, Bin Wang, Mingwen Shao +2

Hybrid action models are widely considered an effective approach to reinforcement learning (RL) modeling. The current mainstream method is to train agents under Parameterized Actio…