How to Choose a Reinforcement-Learning Algorithm
<|reference_start|>How to Choose a Reinforcement-Learning Algorithm: 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/.<|reference_end|>
@article{bongratz2024how,
    title={How to Choose a Reinforcement-Learning Algorithm},
    author={Fabian Bongratz, Vladimir Golkov, Lukas Mautner, Luca Della Libera,
  Frederik Heetmeyer, Felix Czaja, Julian Rodemann, Daniel Cremers},
    journal={arXiv preprint arXiv:2407.20917},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.20917},
    primaryClass={cs.LG cs.AI cs.CV stat.ML}
}