ChainerRL: A Deep Reinforcement Learning Library

2019-12-09 · Yasuhiro Fujita, Prabhat Nagarajan, Toshiki Kataoka, Takahiro Ishikawa

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.

📄 PDF Abstract BibTeX arXiv:1912.03905

Code (1)

chainer/chainerrl 공식 구현 pytorch

Tasks

Deep Reinforcement Learningreinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Pearl: Parallel Evolutionary and Reinforcement Learning Library

2022-01-24 · Rohan Tangri, Danilo P. Mandic, Anthony G. Constantinides

Reinforcement learning is increasingly finding success across domains where the problem can be represented as a Markov decision process. Evolutionary computation algorithms have also proven successful in this domain, exh…

reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Avalanche RL: a Continual Reinforcement Learning Library

2022-02-28 · Nicolò Lucchesi, Antonio Carta, Vincenzo Lomonaco, Davide Bacciu

Continual Reinforcement Learning (CRL) is a challenging setting where an agent learns to interact with an environment that is constantly changing over time (the stream of experiences). In this paper, we describe Avalanch…

Continual Learning OpenAI Gym reinforcement-learning Reinforcement Learning+1

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

2023-12-25 · Wenzhang Liu, Wenzhe Cai, Kun Jiang, Guangran Cheng 외

In this paper, we present XuanCe, a comprehensive and unified deep reinforcement learning (DRL) library designed to be compatible with PyTorch, TensorFlow, and MindSpore. XuanCe offers a wide range of functionalities, in…

CPU Deep Reinforcement Learning GPU MuJoCo+2

RL-X: A Deep Reinforcement Learning Library (not only) for RoboCup

2023-10-20 · Nico Bohlinger, Klaus Dorer

This paper presents the new Deep Reinforcement Learning (DRL) library RL-X and its application to the RoboCup Soccer Simulation 3D League and classic DRL benchmarks. RL-X provides a flexible and easy-to-extend codebase w…

Deep Reinforcement Learning reinforcement-learning Reinforcement Learning

MO-Gym: A Library of Multi-Objective Reinforcement Learning Environments

2022-11-30 · Benelux Conference on Artificial Intelligence BNAIC/BeNeLearn 2022 11 · Lucas N. Alegre, Florian Felten, El-Ghazali Talbi, Grégoire Danoy 외

We introduce MO-Gym, an extensible library containing a diverse set of multi-objective reinforcement learning environments. It introduces a standardized API that facilitates conducting experiments and performance analyse…

Multi-Objective Reinforcement Learning OpenAI Gym reinforcement-learning Reinforcement Learning+1