This is the project video of Sascha Ledermann's bachelor thesis in autumn 2022 at the Bern University of Applied Sciences in Switzerland.
This bachelor thesis shows that an agent can be trained in Unity with MLAgent to run a time trial faster than any human player. Even if the agent drives a route for the first time. For this purpose, an environment is implemented that makes it possible to dynamically create racetracks, drive them and then display statistics and visualizations of the race completed.
In order to be able to optimally train the agent, data is made available in the environment, which the agent can use to record its environment. Care is taken to ensure that the information received does not give him any advantage over a human player.
A reward system is also created for the agent, which enables him to achieve an optimal solution during training. To round off the entire training process, the hyperparameters are evaluated, allowing the agent to perform fast, stable, and efficient training.
Негізгі бет Optimal Racing Car Agent for Unity
Пікірлер: 1