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Deep Reinforcement Learning for Autonomous Driving: A Survey
[article]
2021
arXiv
pre-print
With the development of deep representation learning, the domain of reinforcement learning (RL) has become a powerful learning framework now capable of learning complex policies in high dimensional environments. This review summarises deep reinforcement learning (DRL) algorithms and provides a taxonomy of automated driving tasks where (D)RL methods have been employed, while addressing key computational challenges in real world deployment of autonomous driving agents. It also delineates adjacent
arXiv:2002.00444v2
fatcat:axj3ohhjwzdrxp6dgpfqvctv2i