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A platform for rapid Reinforcement Learning methods development
Application allowing convenient experimentation in Reinforcement Learning - a Machine Learning domain. Project goals are:
- keep adding new environments and agents as simple as possible
- provide a rich set of state-of-art algorithms and problems
- integrate with other existing Reinforcement Learning platforms
If you found this application useful please cite this work: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6643987
In this project we develop algorithms that can solve a cooperative problem between four agent types, and their goal is to repair a surface time-efficiently, and a multi-agent simulator application to parametrize, animate, and test the solution.