rl_reach: Reproducible Reinforcement Learning Experiments for Robotic Reaching Tasks

Training reinforcement learning agents at solving a given task is highly dependent on identifying optimal sets of hyperparameters and selecting suitable environment input / output configurations. This tedious process could be eased with a straightforward toolbox allowing its user to quickly compare...

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Veröffentlicht in:	arXiv.org 2021-03
Hauptverfasser:	Aumjaud, Pierre, McAuliffe, David, Rodríguez Lera, Francisco Javier, Cardiff, Philip
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Learning Computer Science - Robotics Configurations Learning Optimization Source code Training
Online-Zugang:	Volltext
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