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20212024
most citedPlan To Predict: Learning an Uncertainty-Foreseeing Model for Model-Based Reinforcement Learning

4 citations · 8 across the 6 of their papers we have counts for

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cs.LG2024

Policy-regularized Offline Multi-objective Reinforcement Learning

Qian Lin, Chao Yu, Zongkai Liu +1

In this paper, we aim to utilize only offline trajectory data to train a policy for multi-objective RL. We extend the offline policy-regularized method, a widely-adopted approach f…

cs.LG2024

Off-Policy Primal-Dual Safe Reinforcement Learning

Zifan Wu, Bo Tang, Qian Lin +5

Primal-dual safe RL methods commonly perform iterations between the primal update of the policy and the dual update of the Lagrange Multiplier. Such a training paradigm is highly s…