  We present Simion Zoo, a Reinforcement Learning (RL) workbench that provides
a complete set of tools to design, run, and analyze the results,both
statistically and visually, of RL control applications. The main features that
set apart Simion Zoo from similar software packages are its easy-to-use GUI,
its support for distributed execution including deployment over graphics
processing units (GPUs) , and the possibility to explore concurrently the RL
metaparameter space, which is key to successful RL experimentation.

Machine Learning;Artificial Intelligence