rl_rob: A transparent, from-scratch Python library for teaching reinforcement learning from tabular methods to deep policy gradients

Abdulrahman Altahhan

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arXiv · 2610.41303

rl_rob: A transparent, from-scratch Python library for teaching reinforcement learning from tabular methods to deep policy gradients

Abdulrahman Altahhan

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Abstract

rl_rob is an open-source Python library for teaching reinforcement learning. It implements the arc of a modern course, from tabular temporal-difference learning through linear function approximation to deep value-based and policy-gradient methods, with every algorithm written from first principles so that its update rule is visible in a few lines of code. All agents share one interface, so learners can compare methods directly across stages and trace a deep reinforcement learning update from the temporal-difference error to the weight change. The library supports teaching and assessment in which students implement, modify and explain update rules, rather than only produce working code.

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BibTeX RIS

Abdulrahman Altahhan. 2026-10-30. rl_rob: A transparent, from-scratch Python library for teaching reinforcement learning from tabular methods to deep policy gradients. https://arxiv.org/abs/2610.41303

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