Résumé:
A well-thought-out strategy was followed in order to achieve the project's stated objective,
which is to use Reinforcement learning and Unity game engine to create an autonomous parking
simulation. This strategy started with a discussion of various artificial intelligence (AI) subsets
and their methods, followed by a detailed discussion of reinforcement learning, Unity game
engine, and ML-Agents. Finally, we created a simulation using Unity game engine that included
a parking lot as “the environment” and a car as “the agent”, and then we used reinforcement
learning and ML-Agents to train the car to park autonomously