Deep Reinforcement Learning framework for Autonomous Driving

@article{Sallab2017DeepRL,
  title={Deep Reinforcement Learning framework for Autonomous Driving},
  author={Ahmad El Sallab and Mohammed Abdou and Etienne Perot and Senthil Kumar Yogamani},
  journal={ArXiv},
  year={2017},
  volume={abs/1704.02532}
}
  • Ahmad El Sallab, Mohammed Abdou, +1 author Senthil Kumar Yogamani
  • Published 2017
  • Computer Science, Mathematics
  • ArXiv
  • Reinforcement learning is considered to be a strong AI paradigm which can be used to teach machines through interaction with the environment and learning from their mistakes. [...] Key Method It incorporates Recurrent Neural Networks for information integration, enabling the car to handle partially observable scenarios. It also integrates the recent work on attention models to focus on relevant information, thereby reducing the computational complexity for deployment on embedded hardware. The framework was…Expand Abstract

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