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Urban autonomous driving decision making is challenging due to complex road geometry and multi-agent interactions.
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M. Bojarski, P. Yeres, A. Choromanska, K. Choromanski, B. Firner, L. Jackel, and U. Muller · 2017
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Carla: An open urban driving simulator
A. Dosovitskiy, G. Ros, F. Codevilla, A. Lopez, and V. Koltun · 2017
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Deep reinforcement learning framework for autonomous driving
A. E. Sallab, M. Abdou, E. Perot, and S. Yogamani · 2017
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Proximal policy optimization algorithms
J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov · 2017
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Mastering the game of go without human knowledge
D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton, et al · 2017
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Learning how to drive in a real world simulation with deep q-networks
P. Wolf, C. Hubschneider, M. Weber, A. Bauer, J. Härtl, F. Dürr, and J. M. Zöllner · 2017
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
T. Haarnoja, A. Zhou, P. Abbeel, and S. Levine · 2018
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Soft actor-critic algorithms and applications
T. Haarnoja, A. Zhou, K. Hartikainen, G. Tucker, S. Ha, J. Tan, V. Kumar, H. Zhu, A. Gupta, P. Abbeel, et al · 2018
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Alphastar: An evolutionary computation perspective
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Deep imitation learning for autonomous driving in generic urban scenarios with enhanced safety
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