IBM Torcs AI racing competition
Hello readers! Me and my friend Patryk are taking part in the 2026 edition of IBM AI Racing Competition. The goal of it is to develop an AI agent capable of driving a car in Torcs simulator on "Corkscrew" track and perform a full lap. For our solution, we trained an TD3 RL neural network agent to drive the car. Reinforcement Learning networks can control things and learn thru points - in a nutshell, they recieve positive points (reward) for doing something correctly, and negative points (punishment) for doing something incorrectly. They learn how to behave to maximize the reward. Of course, they lack understanding of purpose, so we have to program constrains and how the point system works ourselves. It is challenging, as they like to find workarounds to get free points or stop losing them. If the grading system is designed wrong, the neural network may end up learning to quickly fail or never do anything, for example. First, we pre-trained our network to drive thru the whole...