RLLBC-Lib: An Educational Code Library for Reinforcement Learning and Learning-Based Control
Researchers release RLLBC-Lib, an educational code library covering tabular and deep reinforcement learning with support for automated grading.
RLLBC-Lib is an educational code library aimed at lowering the entry barrier for students learning reinforcement learning in the context of learning-based control. It comprises a comprehensive library of tabular RL approaches, a deep RL library following the same design principles, and implementations contrasting RL with other learning-based control approaches. The library also serves as a basis for creating programming assignments with automated grading.
- Comprehensive tabular RL library enforces understanding of theoretical foundations
- Deep RL library mirrors tabular design principles to show parallels
- Supports programming assignments with automated grading
Full article145 words · extracted from arxiv.org · click to collapse
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 theoretical foundations. A deep RL library follows the same design principles, underscoring the parallels between simple tabular and state-of-the-art deep RL approaches. Additionally, RLLBC-Lib provides a collection of implementations illustrating core RL principles and contrasting RL to other learning-based control approaches. Finally, RLLBC-Lib provides an ideal basis for creating programming assignments with automated grading.
Text extracted automatically; images, tables and formatting may be missing. Original: https://arxiv.org/abs/2609.19074