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...With Unity Machine Learning Agents (ML-Agents), you are no longer “coding” emergent behaviors, but rather teaching intelligent agents to “learn” through a combination of deep reinforcement learning and imitation learning. Using ML-Agents allows developers to create more compelling gameplay and an enhanced game experience. Advancement of artificial intelligence (AI) research depends on figuring out tough problems in existing environments using current benchmarks for training AI models. Using Unity and the ML-Agents toolkit, you can create AI environments that are physically, visually, and cognitively rich.

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

This is a third year computer science project. A software system for simulating and animating Reinforcement Learning (RL) algorithms mainly for modular robots.