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Rei - Capstone Blog Post 2



This week, I wanted to look more deeply at current game AIs and try to get a deeper understanding of what Machine Learning AIs created for video games look like. I started by looking at one of the larger Computer Vision AIs, ViZDoom.




ViZDoom, according to the official website, is a "Doom-based AI research platform for reinforcement learning from raw visual information." ViZDoom sets out to accomplish a goal similar to ours, make an AI that can play Doom using only the screen buffer. The research group holds annual competitions, the competitions allows many developers to test their AI tweaks against others which results in some pretty competent AI players.


After looking into ViZDoom and learning about more Algorithms in AI, I decided to look at some of the really amazing Game AIs that are coming into public view. I found a video that explained AlphaGo. Which I found that I understood, at least understood better than I would have earlier. AlphaGo's math is pretty much a MiniMax algorithm and neural networks.


While I still don't completely understand everything explained in this video, I can tell that I am much closer than I was even last week. Now that I have at least implements some simple AIs(Basic Graph Searches), I understand how the data flow works a bit better.

My goals moving forward are to take a more in-depth look at simple neural networks. I would like to understand, at the very least, how data is stored and flows in a Neural Network problem. The other major goal I have for the upcoming weeks is to start listing the skills and resources that will be needed to complete this project.
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