Now that we have discussed the theory behind the game-playing agent's implementation, we are ready to start working on it. Our implementation is based on the source code provided by the Uber AI Lab on GitHub at https://github.com/uber-research/deep-neuroevolution. The source code in this repository contains an implementation of two methods to train DNNs: the CPU-based methods for multicore systems (up to 720 cores) and the GPU-based methods. We are interested in the GPU-based implementation because the majority of practitioners don't have access to such behemoths of technology as a PC with 720 CPU cores. At the same time, it is pretty easy to get access to a modern Nvidia GPU.
Next, we'll discuss the implementation details.
