3 citations · 9 across the 10 of their papers we have counts for
5 papers · 1 filter
Continual Task Learning through Adaptive Policy Self-Composition
Shengchao Hu, Yuhang Zhou, Ziqing Fan +4
Training a generalizable agent to continually learn a sequence of tasks from offline trajectories is a natural requirement for long-lived agents, yet remains a significant challeng…
Solving Continual Offline RL through Selective Weights Activation on Aligned Spaces
Jifeng Hu, Sili Huang, Li Shen +7
Continual offline reinforcement learning (CORL) has shown impressive ability in diffusion-based lifelong learning systems by modeling the joint distributions of trajectories. Howev…
Continual Diffuser (CoD): Mastering Continual Offline Reinforcement Learning with Experience Rehearsal
Jifeng Hu, Li Shen, Sili Huang +5
Artificial neural networks, especially recent diffusion-based models, have shown remarkable superiority in gaming, control, and QA systems, where the training tasks' datasets are u…
Decision Mamba: Reinforcement Learning via Hybrid Selective Sequence Modeling
Sili Huang, Jifeng Hu, Zhejian Yang +5
Recent works have shown the remarkable superiority of transformer models in reinforcement learning (RL), where the decision-making problem is formulated as sequential generation. T…
In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought
Sili Huang, Jifeng Hu, Hechang Chen +2
In-context learning is a promising approach for offline reinforcement learning (RL) to handle online tasks, which can be achieved by providing task prompts. Recent works demonstrat…