AINeutralarXiv – CS AI · 8h ago6/10
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Path-Coupled Bellman Flows for Distributional Reinforcement Learning
Researchers propose Path-Coupled Bellman Flows (PCBF), a novel distributional reinforcement learning method that addresses limitations in existing flow-based approaches by using source-consistent paths and shared noise coupling to improve training stability and return distribution fidelity. The approach demonstrates competitive performance on benchmark tasks while maintaining computational efficiency through variance-reduction techniques.