Wurman2022 - Outracing champion Gran Turismo drivers with deep reinforcement learning

• Type:#article
• Year read:#read2022
• Subject:
• Bibtex: @wurman2022
• Bibliography: Wurman, P. R., Barrett, S., Kawamoto, K., MacGlashan, J., Subramanian, K., Walsh, T. J., Capobianco, R., Devlic, A., Eckert, F., Fuchs, F., Gilpin, L., Khandelwal, P., Kompella, V., Lin, H., MacAlpine, P., Oller, D., Seno, T., Sherstan, C., Thomure, M. D., … Kitano, H. (2022). Outracing champion Gran Turismo drivers with deep reinforcement learning. Nature, 602(7896), 223–228. https://doi.org/10.1038/s41586-021-04357-7

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Example citation §

Key takeaways §

• They trained an AI to not just race competitively, but to also follow the unofficial rules of sportsmanship.
• Deep reinforcement learning
• Two dimensions of control: accelerate/brake and steering left/right

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https://youtu.be/l948hMaTPuo

This is an interesting contrast to If you only care about the binary outcome (win or loss) you dont have to win by a large margin like in Go, because here they wanted to place many cars near the top and also adhere to the game’s unofficial sportsmanship rules.