This blog post will first present the environment of this experiment. Now, the scope is much bigger than a single jump: I want the AI to learn how to navigate through the entire race! Learning Excitebike follows a blog post that I’ve made some years ago where I sampled random trials of a single jump. I choose to make the AI learn to play the NES game Excitebike. Being more familiar with Gradient Boosting techniques than Neural Networks, I decided to give the method a chance. Recently, I stumbled upon this paper which outline a method for making an AI learn to play video games using a Gradient Boosting algorithm. This is not the only case, as there are multiple games played by AI that can be found on the Internet: Super Mario World, Pac-Man, Super Mario Kart, etc. A notable effort came from Deepmind with a Convolutional Neural Network algorithm that can play an handful of Atari 2600 games. This incredible development now even extends to video games. For example, it has learn to drive cars, translate languages, understand pictures, filter emails, etc. Following the incredible boost in machine learning applications in the recent years, people have made artificial intelligence (AI) learn many tasks.
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