5 citations · 7 across the 5 of their papers we have counts for
5 papers
Latent Reward: LLM-Empowered Credit Assignment in Episodic Reinforcement Learning
Yun Qu, Yuhang Jiang, Boyuan Wang +4
Reinforcement learning (RL) often encounters delayed and sparse feedback in real-world applications, even with only episodic rewards. Previous approaches have made some progress in…
Near-Optimal Regret Bounds for Multi-batch Reinforcement Learning
Zihan Zhang, Yuhang Jiang, Yuan Zhou +1
In this paper, we study the episodic reinforcement learning (RL) problem modeled by finite-horizon Markov Decision Processes (MDPs) with constraint on the number of batches. The mu…
Reducing Conservativeness Oriented Offline Reinforcement Learning
Hongchang Zhang, Jianzhun Shao, Yuhang Jiang +2
In offline reinforcement learning, a policy learns to maximize cumulative rewards with a fixed collection of data. Towards conservative strategy, current methods choose to regulari…
Credit Assignment with Meta-Policy Gradient for Multi-Agent Reinforcement Learning
Jianzhun Shao, Hongchang Zhang, Yuhang Jiang +2
Reward decomposition is a critical problem in centralized training with decentralized execution~(CTDE) paradigm for multi-agent reinforcement learning. To take full advantage of gl…
PFRL: Pose-Free Reinforcement Learning for 6D Pose Estimation
Jianzhun Shao, Yuhang Jiang, Gu Wang +2
6D pose estimation from a single RGB image is a challenging and vital task in computer vision. The current mainstream deep model methods resort to 2D images annotated with real-wor…