2022
JMLR
JMLR 2022
Tianshou: A Highly Modularized Deep Reinforcement Learning Library
Abstract
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-friendly by providing a flexible and reliable infrastructure of DRL algorithms. It supports online and offline training with more than 20 classic algorithms through a unified interface. To facilitate related research and prove Tianshou's reliability, we have released Tianshou's benchmark of MuJoCo environments, covering eight classic algorithms with state-of-the-art performance. We open-sourced Tianshou at https://github.com/thu-ml/tianshou/. [abs] [ pdf ][ bib ] [ code ] © JMLR 2022. (edit, beta)
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Jiayi Weng
,
Huayu Chen
,
Dong Yan
,
Kaichao You
,
Alexis Duburcq
,
Minghao Zhang
,
Yi Su
,
Hang Su
,
Jun Zhu