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

Simion Zoo: A Workbench for Distributed Experimentation with Reinforcement Learning for Continuous Control Tasks