Author

Weidong Zhao

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Jul 2026

Collaborative Weighting with Pessimistic Critic for Mitigating Overestimation in Off-Policy Reinforcement Learning

This paper proposes Collaborative Weighting Actor-Critic (CWAC), a unified framework that explicitly accounts for predictive uncertainty in value estimation and introduces a collaborative weighting mechanism that jointly reweights TD-errors and uncertainty, enabling robust learning from reliable samples while suppressi...

Gong Gao, Xiao Lai, Zi-Qi Xie et al. · arXiv.org · 0 citations

#machine learning Open access Aug 2026

Improving Generalization and Robustness in Offline Reinforcement Learning via Boundary-Aware Data Augmentation

Qualitative studies in a toy environment show that BADA generates mixed samples that preserve desirable policy smoothness while accurately reconstructing multimodal value distributions, and extensive experiments on limited offline datasets further demonstrate that BADA attains state-of-the-art performance across divers...

Gong Gao, Weidong Zhao, Xianhui Liu · IEEE Transactions on Knowled... · 0 citations

#machine learning Preprint Jul 2026

Improving Online Reinforcement Learning via Bidirectional Behavior Prior Distillation

This work shows that enforcing high-quality behavioral support during online learning effectively mitigates critic-induced error amplification, enabling structured behavior priors to guide policy updates in a principled and sample-efficient manner.

Gong Gao, Xiao Lai, Jia-Ji Shen et al. · 0 citations

Open access Jul 2026

Expert Behavior Prior Reinforcement Learning

A Q-guided conditional variational autoencoder (Q-CVAE) is introduced that learns to generate expert policy priors directly from the online replay buffer, enabling the generation of high-value actions for guiding policy updates without relying on precollected expert trajectories.

Gong Gao, Weidong Zhao, Xianhui Liu et al. · IEEE Transactions on Neural... · 0 citations