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This project is mantained by the Group of Computational Intelligence (University of the Basque Country - UPV/EHU): http://www.ehu.eus/ccwintco
Our goal is to build a Reinforcement Learning experimenting environment in which the user can conduct experiments using a GUI without needing to code, install any dependecies, or run a configuration process.
The focus of the project is set on solving control problems with continuous action and states using Reinforcement Learning methods. The main features of the project can be summarized:
- Parameter sweeps using 'forks' on the parameters
- Real-time and off-line experiment visualization
- Built-in result analysis tools
- Distributed execution of experiments (distribution is done via the 'forks')
In the wiki you can find information about how to get started with this project, either as an user or as a developer.
This project has been mainly contributed by Unai Tercero, Asier Rodriguez, Roland Zimmermann, José Alejandro Guerra Denis and Borja Fernández Gauna.