MushroomRL: Simplifying Reinforcement Learning Research
This tool addresses the need for a flexible and comprehensive framework to streamline RL research, though it is incremental compared to existing libraries.
The authors introduced MushroomRL, an open-source Python library designed to simplify the implementation and testing of reinforcement learning experiments, enabling researchers to focus more on developing novel algorithms.
MushroomRL is an open-source Python library developed to simplify the process of implementing and running Reinforcement Learning (RL) experiments. Compared to other available libraries, MushroomRL has been created with the purpose of providing a comprehensive and flexible framework to minimize the effort in implementing and testing novel RL methodologies. Indeed, the architecture of MushroomRL is built in such a way that every component of an RL problem is already provided, and most of the time users can only focus on the implementation of their own algorithms and experiments. The result is a library from which RL researchers can significantly benefit in the critical phase of the empirical analysis of their works. MushroomRL stable code, tutorials and documentation can be found at https://github.com/MushroomRL/mushroom-rl.