Tianshou: a Highly Modularized Deep Reinforcement Learning Library
This provides a flexible and reliable tool for researchers in reinforcement learning, though it is incremental as it builds on existing algorithms.
The authors introduced Tianshou, a modular Python library for deep reinforcement learning using PyTorch, which supports over 20 algorithms and achieves state-of-the-art performance in MuJoCo benchmarks.
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/.