A workflow for offline model-free robotic reinforcement learning

A Kumar, A Singh, S Tian, C Finn, S Levine - arXiv preprint arXiv …, 2021 - arxiv.org
Offline reinforcement learning (RL) enables learning control policies by utilizing only prior
experience, without any online interaction. This can allow robots to acquire generalizable …
被引用次数：85 相关文章
[PDF] academia.edu

[PDF][PDF] A Workflow for Offline Model-Free Robotic Reinforcement Learning

A Kumar, A Singh, S Tian, C Finn, S Levine - academia.edu
Offline reinforcement learning (RL) enables learning control policies by utilizing only prior
experience, without any online interaction. This can allow robots to acquire generalizable …

A Workflow for Offline Model-Free Robotic Reinforcement Learning

A Kumar, A Singh, S Tian, C Finn, S Levine - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
Offline reinforcement learning (RL) enables learning control policies by utilizing only prior
experience, without any online interaction. This can allow robots to acquire generalizable …

A Workflow for Offline Model-Free Robotic Reinforcement Learning

A Kumar, A Singh, S Tian, C Finn… - Conference on Robot …, 2022 - proceedings.mlr.press
Offline reinforcement learning (RL) enables learning control policies by utilizing only prior
experience, without any online interaction. This can allow robots to acquire generalizable …

A Workflow for Offline Model-Free Robotic Reinforcement Learning

A Kumar, A Singh, S Tian, C Finn, S Levine - 5th Annual Conference on … - openreview.net
Offline reinforcement learning (RL) enables learning control policies by utilizing only prior
experience, without any online interaction. This can allow robots to acquire generalizable …

A Workflow for Offline Model-Free Robotic Reinforcement Learning

A Kumar, A Singh, S Tian, C Finn… - Conference on Robot …, 2022 - proceedings.mlr.press
Offline reinforcement learning (RL) enables learning control policies by utilizing only prior
experience, without any online interaction. This can allow robots to acquire generalizable …