2020
Steep: Imitation Learning to Complete Ski Races
Steep is an open-world winter sports game that allows players to participate in downhill skiing races, among other activities. Because of the open-world design, I was interested in trying to create a neural network that could complete the different races. I trained a neural network using imitation learning, creating training data from my own gameplay and augmenting it to create a sizable training set. How close to human performance can we achieve from a neural network trained using imitation learning?
Steep Part 2: Imitation Learning to Complete Rocket Suit Races
After spending considerable effort developing a data collection and processing pipeline, the ski neural network was able to perform well on a simple course. There exists a separate race mode in Steep using a rocket suit that allows a set of guidelines that can be toggled. However the rocket suit races require more controls to navigate the course and are much less forgiving. Is the additional visual information sufficient to allow a network trained through imitation learning to navigate the course?
