1. A survey of inverse reinforcement learning: Challenges, methods and progress
2. Mayank Bansal , Alex Krizhevsky , and Abhijit Ogale . 2018 . Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst. arXiv preprint arXiv:1812.03079 (2018). Mayank Bansal, Alex Krizhevsky, and Abhijit Ogale. 2018. Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst. arXiv preprint arXiv:1812.03079 (2018).
3. Luca Bergamini , Yawei Ye , Oliver Scheel , Long Chen , Chih Hu , Luca Del Pero , Błażej Osiński , Hugo Grimmett , and Peter Ondruska . 2021 . Simnet: Learning reactive self-driving simulations from real-world observations . In 2021 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 5119–5125 . Luca Bergamini, Yawei Ye, Oliver Scheel, Long Chen, Chih Hu, Luca Del Pero, Błażej Osiński, Hugo Grimmett, and Peter Ondruska. 2021. Simnet: Learning reactive self-driving simulations from real-world observations. In 2021 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 5119–5125.
4. SimNet: Learning Reactive Self-driving Simulations from Real-world Observations
5. Julian Bernhard , Klemens Esterle , Patrick Hart , and Tobias Kessler . 2020 . BARK: Open behavior benchmarking in multi-agent environments . In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 6201–6208 . Julian Bernhard, Klemens Esterle, Patrick Hart, and Tobias Kessler. 2020. BARK: Open behavior benchmarking in multi-agent environments. In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 6201–6208.