An episode of a pre-trained Rainbow model.

In a previous post, I gave a high-level overview of PFRL (Preferred RL), an open source deep reinforcement learning (RL) library. In this short post, I’ll show how you can easily load PFRL’s pre-trained models.

Currently, PFRL has pre-trained models for all algorithms for which it has reproducibility scripts, which are scripts that are intended to reproduce the original algorithm’s published results as closely as possible. In particular, as of this writing, PFRL has reproducibility scripts for 9 key deep RL algorithms: A3C, DQN, IQN, Rainbow, DDPG, TRPO, PPO, TD3, and SAC.

Depending on the algorithm, PFRL has up to…

PFRL(“Preferred RL”) is a PyTorch-based open-source deep Reinforcement Learning (RL) library developed by Preferred Networks (PFN). PFN is the company behind the deep learning library Chainer and the ChainerRL library to which PFRL is the PyTorch-based successor.


Oftentimes, when starting a new research project, obtaining or producing quality baseline algorithms can be the first — and sometimes the main — hurdle to overcome. This is especially the case when aiming to surpass state-of-the-art performance, when sometimes neither public nor private implementations are able to reproduce the current state-of-the-art performance. …

Prabhat Nagarajan

Reinforcement Learning PhD Student at UAlberta

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