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@article{IEEE-IS22,
  author={Peter R.\ Wurman and Peter Stone and Michael Sprannger},
  journal="{IEEE} {I}ntelligent {S}ystems", 
  title="Challenges and Opportunities of Applying Reinforcement Learning to Autonomous Racing",
  year={2022},
  month={May-June},
  volume={37},
  number={3},
  pages={20--3},
  abstract="Simulated motorsports are an exciting environment in which
            to explore the power and limitations of deep reinforcement
            learning. Racing requires precise control of a vehicle
            that is operating at its traction limits while competing
            wheel-to-wheel with other drivers. We recently
            demonstrated an agent that can beat the best drivers in
            the world at the racing game Gran Turismo. In this
            article, we briefly discuss some of the lessons learned
            and some of the remaining open research challenges.",
  wwwnote={<a href="https://ieeexplore.ieee.org/abstract/document/9839480">Official online version</a>},
}