Reinforcement Learning with Unity 3D

This was start of a great journey, which required us to use our knowledge from the fields of Computer Vision, Deep Reinforcement Learning and Game Development to create a functional simulation of our robot, G.E.A.R – Garbage Evaporating Autonomous Robot. Naturally, if you would like to tinker with the G.E.A.R or contribute further to our project, feel free to visit the repository: Reinforcement Learning With Unity-G.E.A.R.

No matter where you come from – the first things which comes to mind when you hear about Munich, the capital of Bavaria, is Oktoberfest. Those may not be applicable to all RL project, but should be kept in mind if you struggle with the similar tasks as ours:

First, try to get “good enough” policy quickly – we have noticed, that it is advisable to first present the agent with high rewards for the main goal, while giving only small (or no) feedback signals regarding secondary goals.

Source: dtransposed.github.io