This paper introduces RL-Studio, an open-source software that eases the implementation of reinforcement learning algorithms to solve a problem. This software enables the integration of any simulator to recreate the problem where a reinforcement learning algorithm can be applied. Some relevant advantages of this tool are the generalization of common software components and the unified architecture. RL-Studio permits to just focus on fine tuning the hyperparameters of the algorithm and redefine the goal and reward function of the previously integrated projects. In case a non-integrated scenario, algorithm or simulator is needed, RL-Studio also provides some already integrated libraries that can be reused to save time. It has been experimentally validated in research projects and some of the canonical problems such as Robot Mesh or Mountain Car.
RL-Studio: A Tool for Reinforcement Learning Methods in Robotics
Lect. Notes in Networks, Syst.
Iberian Robotics conference ; 2022 ; Zaragoza, Spain November 23, 2022 - November 25, 2022
2022-11-19
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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