swMATH ID: 31150
Software Authors: Yasuhiro Fujita, Toshiki Kataoka, Prabhat Nagarajan, Takahiro Ishikawa
Description: ChainerRL: A Deep Reinforcement Learning Library. 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 the 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
Homepage: https://arxiv.org/abs/1912.03905
Source Code:  https://github.com/chainer/chainerrl
Keywords: Machine Learning; arXiv_cs.LG; Artificial Intelligence; arXiv_cs.AI; arXiv_stat.ML; Deep Reinforcement Learning; DRL; Python
Related Software: rlpyt; Dopamine; Stable Baselines; Catalyst.RL; PyTorch; RLlib; OpenAI Gym; Python; GitHub; d3rlpy; Pybullet; Scikit; Tonic; MuJoCo; Pwnagotchi; Imitation; SLM Lab; TF-Agents; WaveRL; Stable Baselines3
Cited in: 2 Publications

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2 Publications describing the Software, including 1 Publication in zbMATH Year
ChainerRL: a deep reinforcement learning library. Zbl 07370594
Fujita, Yasuhiro; Nagarajan, Prabhat; Kataoka, Toshiki; Ishikawa, Takahiro
ChainerRL: A Deep Reinforcement Learning Library
Yasuhiro Fujita, Toshiki Kataoka, Prabhat Nagarajan, Takahiro Ishikawa

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