5 papers · 1 filter
Koopman Dreamer: Spectrally Constrained Latent Dynamics for Stable World-Model Imagination
Jiaqi Li, Xinglong Zhang, Haibin Xie +3
Latent world models improve sample efficiency in continuous control by optimizing policies over imagined latent trajectories, but common neural transitions offer limited direct con…
SD2AIL: Adversarial Imitation Learning from Synthetic Demonstrations via Diffusion Models
Pengcheng Li, Qiang Fang, Tong Zhao +2
Adversarial Imitation Learning (AIL) is a dominant framework in imitation learning that infers rewards from expert demonstrations to guide policy optimization. Although providing m…
Diffusion Policies with Value-Conditional Optimization for Offline Reinforcement Learning
Yunchang Ma, Tenglong Liu, Yixing Lan +4
In offline reinforcement learning, value overestimation caused by out-of-distribution (OOD) actions significantly limits policy performance. Recently, diffusion models have been le…
Skill Expansion and Composition in Parameter Space
Tenglong Liu, Jianxiong Li, Yinan Zheng +4
Humans excel at reusing prior knowledge to address new challenges and developing skills while solving problems. This paradigm becomes increasingly popular in the development of aut…
Adaptive Advantage-Guided Policy Regularization for Offline Reinforcement Learning
Tenglong Liu, Yang Li, Yixing Lan +3
In offline reinforcement learning, the challenge of out-of-distribution (OOD) is pronounced. To address this, existing methods often constrain the learned policy through policy reg…