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JMLR-2009

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

Brian Tanner and Adam White. RL-Glue: Language-Independent Software for Reinforcement-Learning Experiments. Journal of Machine Learning Research, 10(Sep):2133--2136, 2009.

A preprint of this publication is attached to this page. Official paper homepage is here: http://mloss.org/software/view/151/

Abstract

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.

BibTeX Entry

@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}}
Ċ
Brian Tanner,
Sep 19, 2010, 5:17 PM
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