Diffusion policies as an expressive policy class for offline reinforcement learning[J]. arXiv preprint arXiv:2208.06193, 2022. arxiv.org/pdf/2208.0619 1.离线强化学习的挑战:离线强化学习面临的主要挑战是什么? (ABSTRACT) 离线强化学习面临的主要挑战是在不与环境进行实时交互的情况下,从已经收集的静态数据...
Abstract在本文中,作者将强化学习中policy看作了一个Diffusion model(扩散模型), 提出了Diffusion Q-learning(Diffusion-QL)算法。Diffusion-QL利用Condition Diffusion model(条件扩散模型)来表示策略。通过学习…
Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning Zhendong Wang, Jonathan J Hunt and Mingyuan Zhou https://arxiv.org/abs/2208.06193 Abstract: Offline reinforcement learning (RL), which aims to learn an optimal policy using a previously collected static dataset, is...
"Diffusion policies as an expressive policy class for offline reinforcement learning." International Conference on Learning Representations. 2023. Brehmer, Johann, et al. "EDGI: Equivariant Diffusion for Planning with Embodied Agents." arXiv preprint arXiv:2303.12410 (2023). Chen, Huayu, et al. "...
Put briefly, proponents of this view assert that, whatever the merits of affirmative-action type policies in other remedial contexts, there is something distinctly and profoundly troubling about using race to design the fundamental democratic institutions of the State. On this view, a practice of ...
Codebase for OA-ReactDiff is available as an open-source repository on GitHub for contiguous development,https://github.com/chenruduan/OAReactDiff. A stable version of the code56used in this work is available at Zenodo,https://doi.org/10.5281/zenodo.10054963. ...
Diffusion-QL-DIFFUSION POLICIES AS AN EXPRESSIVE POLICY CLASS FOR OFFLINE REINFORCEMENT LEARNING Motivation offline RL会访问OOD动作,因为这样会导致价值函数估计不准确,故将对性能产生影响。以前缓解该问题的方式包括:① 对策略学习目标进行约束,使其接近行为策略;② 约束价值函数,使其对OOD动作进行低估;③ 引入...
Wang, Zhendong, Jonathan J. Hunt, and Mingyuan Zhou. "Diffusion policies as an expressive policy class for offline reinforcement learning."arXiv preprint arXiv:2208.06193(2022). Motivation 利用Diffusion model的高拟合能力(expressive)来引导策略与数据集对齐,缓解OOD问题。
There is another way: "Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning" by Wang, Z. proposed Diffusion Model as policy-optimization in offline RL, et al. Specifically, Diffusion-QL forms policy as a conditional diffusion model with states as the condition from ...
Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning Zhendong Wang, Jonathan J Hunt, Mingyuan Zhou arXiv 2022. [Paper] [Github] 12 Oct 2022 Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling Huayu Chen, Cheng Lu, Chengyang Ying, Hang Su...