This project aims to use a combination of imitation learning and reinforcement learning in order to play Asseto Corsa by learning new policies from expert samples and reward function. These policies are a combination of a function of minimizing the difference between expert moves and the maximizing the reward.
☆20Sep 10, 2020Updated 5 years ago
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