dotRL: A platform for rapid Reinforcement Learning methods development and validation

This paper introduces dotRL, a platform that enables fast implementation and testing of Reinforcement Learning algorithms against diverse environments. dotRL has been written under .NET framework and its main characteristics include: (i) adding a new learning algorithm or environment to the platform only requires implementing a simple interface, from then on it is ready to be coupled with other environments and algorithms, (ii) a set of tools is included that aid running and reporting experiments, (iii) a set of benchmark environments is included, with as demanding as Octopus-Arm and Half-Cheetah, (iv) the platform is available for instantaneous download, compilation, and execution, without libraries from different sources.