arXiv Machine Learning August 12, 2026 By Zefeng Liang, Jie Qiao, Ruichu Cai, Weilin Chen, Zhifeng Hao

IADD-TR: Intervention-Aware Dynamics Decoupling with Targeted Regularization for Model-Based Reinforcement Learning

Read the original on arXiv Machine Learning →

arXiv:2608. 10634v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL), which learns environment dynamics to generate synthetic experience, is a promising approach to sample-efficient decision making.

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