2009 JMLR JMLR 2009

RL-Glue: Language-Independent Software for Reinforcement-Learning Experiments

Abstract

RL-Glue is a standard, language-independent software package for reinforcement-learning experiments. The standardization provided by RL-Glue facilitates code sharing and collaboration. Code sharing reduces the need to re-engineer tasks and experimental apparatus, both common barriers to comparatively evaluating new ideas in the context of the literature. Our software features a minimalist interface and works with several languages and computing platforms. RL-Glue compatibility can be extended to any programming language that supports network socket communication. RL-Glue has been used to teach classes, to run international competitions, and is currently used by several other open-source software and hardware projects. [abs] [ pdf ][ bib ] [ code ] © JMLR 2009. (edit, beta)

🌉 Interdisciplinary Bridge — Computer Science and Machine Learning
📈 Trend Setter — Software Engineering
🧭 Keyword Pioneer — software framework
🐣 Hot Topic Early Bird — reinforcement learning
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio