How to Choose a Reinforcement-Learning Algorithm

Fabian Bongratz; Vladimir Golkov; Lukas Mautner; Luca Della Libera; Frederik Heetmeyer; Felix Czaja; Julian Rodemann; Daniel Cremers

arXiv · 2407.20917

How to Choose a Reinforcement-Learning Algorithm

Fabian Bongratz·Vladimir Golkov·Lukas Mautner·Luca Della Libera·Frederik Heetmeyer·Felix Czaja·Julian Rodemann·Daniel Cremers

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Abstract

The field of reinforcement learning offers a large variety of concepts and methods to tackle sequential decision-making problems. This variety has become so large that choosing an algorithm for a task at hand can be challenging. In this work, we streamline the process of choosing reinforcement-learning algorithms and action-distribution families. We provide a structured overview of existing methods and their properties, as well as guidelines for when to choose which methods. An interactive version of these guidelines is available online at https://rl-picker.github.io/.

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Fabian Bongratz, Vladimir Golkov, Lukas Mautner, Luca Della Libera, Frederik Heetmeyer, Felix Czaja, Julian Rodemann, Daniel Cremers. 2024-07-30. How to Choose a Reinforcement-Learning Algorithm. https://arxiv.org/abs/2407.20917

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