The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/5ce26dac-4323-4c5d-9fe3-157dc17bed12

van der Vaart, Pascal (2025): Epistemic Bellman Operators; code underlying the dissertation ‘Bayesian Model-Free Deep Reinforcement Learning’. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/5ce26dac-4323-4c5d-9fe3-157dc17bed12.v1

Categories

• Artificial Intelligence and Image Processing
• Information and Computing Sciences

Keywords

Bayesian modelling Deep Reinforcement Learning (DRL) Dynamic Programming Machine Learning (ML) Uncertainty quantification

Licence

MIT

Interoperability

• RO-Crate Metadata

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by Pascal van der Vaart

Code underlying dissertation work "Bayesian Model-Free Deep Reinforcement Learning". This data set contains code for reproducing the experiments conducted in the chapter "Epistemic Bellman Operators", with the goal of validating the mathematical theory in the chapter. The code has no applications other than supporting the mathematical theory.

History

• 2025-08-11 first online, published, posted

Publisher

4TU.ResearchData

Format

.py, .ipynb

Associated peer-reviewed publication

Epistemic Bellman Operators

Code hosting project url

https://github.com/Pascal314/epistemic-bellman-operators

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Intelligent Systems