SOURCE-LINKED INTELLIGENCE
RLLBC-Lib: An Educational Code Library for Reinforcement Learning and Learning-Based Control
Reinforcement learning (RL) is an exciting concept as well as a remarkable success story worth sharing. However, RL builds on rather complex interactions between different objects that play out over several cycles. Such dynamics are often best explained with an easily accessible implementation. We present RLLBC-Lib, a carefully crafted code library with the goal of lowering the entry barrier for students and other learners of RL in the context of learning-based control. At its heart, RLLBC-Lib comprises a comprehensive library of tabular RL approaches to enforce a clear understanding of the th
Read original source ↗ Open in workspace
- recordType
- paper
- region
- Global
Evidence & attribution
- arXiv · Artificial Intelligence · 2026-09-16T17:15:59.000Z
- arXiv · AI, language, vision and robotics · 2026-09-16T17:15:59.000Z
First collected: 2026-09-19T20:26:32.566Z. This is not the publication date.