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JMLR 2021

ChainerRL: A Deep Reinforcement Learning Library

Journal Article Articles Artificial Intelligence ยท Machine Learning

Abstract

In this paper, we introduce ChainerRL, an open-source deep reinforcement learning (DRL) library built using Python and the Chainer deep learning framework. ChainerRL implements a comprehensive set of DRL algorithms and techniques drawn from state-of-the-art research in the field. To foster reproducible research, and for instructional purposes, ChainerRL provides scripts that closely replicate the original papers' experimental settings and reproduce published benchmark results for several algorithms. Lastly, ChainerRL offers a visualization tool that enables the qualitative inspection of trained agents. The ChainerRL source code can be found on GitHub: https://github.com/chainer/chainerrl. [abs] [ pdf ][ bib ] [ code ] &copy JMLR 2021. ( edit, beta )

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Context

Venue
Journal of Machine Learning Research
Archive span
2000-2026
Indexed papers
4180
Paper id
526876578490858765
v2026.09.13