A preprint of this publication is attached to this page. Official paper homepage is here: http://mloss.org/software/view/151/
RL-Glue is a standard, language-independent software package for reinforcement-learning experi- ments. 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 compat- ibility 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.
@article{rl-glue, Author = {Brian Tanner and Adam White}, Journal = {Journal of Machine Learning Research}, Month = {September}, Pages = {2133--2136}, Title = {{RL}-{G}lue : Language-Independent Software for Reinforcement-Learning Experiments}, Volume = {10}, Year = {2009}}