most citedTianshou: a Highly Modularized Deep Reinforcement Learning Library

116 citations · 151 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2021

Vision-Guided Quadrupedal Locomotion in the Wild with Multi-Modal Delay Randomization

Chieko Sarah Imai, Minghao Zhang, Yuchen Zhang +4

Developing robust vision-guided controllers for quadrupedal robots in complex environments, with various obstacles, dynamical surroundings and uneven terrains, is very challenging.…

cs.LG2021★ 116 cited

Tianshou: a Highly Modularized Deep Reinforcement Learning Library

Jiayi Weng, Huayu Chen, Dong Yan +6

In this paper, we present Tianshou, a highly modularized Python library for deep reinforcement learning (DRL) that uses PyTorch as its backend. Tianshou intends to be research-frie…

cs.LG2021★ 27 cited

Learning Vision-Guided Quadrupedal Locomotion End-to-End with Cross-Modal Transformers

Ruihan Yang, Minghao Zhang, Nicklas Hansen +2

We propose to address quadrupedal locomotion tasks using Reinforcement Learning (RL) with a Transformer-based model that learns to combine proprioceptive information and high-dimen…

cs.LG2021★ 2 cited

DAIR: Disentangled Attention Intrinsic Regularization for Safe and Efficient Bimanual Manipulation

Minghao Zhang, Pingcheng Jian, Yi Wu +2

We address the problem of safely solving complex bimanual robot manipulation tasks with sparse rewards. Such challenging tasks can be decomposed into sub-tasks that are accomplisha…

cs.LG2020★ 6 cited

Bridging Imagination and Reality for Model-Based Deep Reinforcement Learning

Guangxiang Zhu, Minghao Zhang, Honglak Lee +1

Sample efficiency has been one of the major challenges for deep reinforcement learning. Recently, model-based reinforcement learning has been proposed to address this challenge by…