ARC: Adversarially Robust Control Policies for Autonomous Vehicles
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[1] Mykel J. Kochenderfer,et al. Adaptive Stress Testing for Autonomous Vehicles , 2018, 2018 IEEE Intelligent Vehicles Symposium (IV).
[2] Junmo Kim,et al. Less-forgetful Learning for Domain Expansion in Deep Neural Networks , 2017, AAAI.
[3] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[4] Stefano Ermon,et al. Generative Adversarial Imitation Learning , 2016, NIPS.
[5] Richard Bowden,et al. Training Adversarial Agents to Exploit Weaknesses in Deep Control Policies , 2020, 2020 IEEE International Conference on Robotics and Automation (ICRA).
[6] Arslan Munir,et al. Adversarial Reinforcement Learning Framework for Benchmarking Collision Avoidance Mechanisms in Autonomous Vehicles , 2018, IEEE Intelligent Transportation Systems Magazine.
[7] Yang Gao,et al. Risk Averse Robust Adversarial Reinforcement Learning , 2019, 2019 International Conference on Robotics and Automation (ICRA).
[8] Gert Kootstra,et al. International Conference on Robotics and Automation (ICRA) , 2008, ICRA 2008.
[9] Xin Zhang,et al. End to End Learning for Self-Driving Cars , 2016, ArXiv.
[10] Geoffrey E. Hinton,et al. Distilling the Knowledge in a Neural Network , 2015, ArXiv.
[11] Sergey Levine,et al. End-to-End Training of Deep Visuomotor Policies , 2015, J. Mach. Learn. Res..
[12] Abhinav Gupta,et al. Robust Adversarial Reinforcement Learning , 2017, ICML.
[13] Jürgen Schmidhuber,et al. World Models , 2018, ArXiv.
[14] Alan L. Yuille,et al. Feature Denoising for Improving Adversarial Robustness , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[15] Bruno Scherrer,et al. Approximate Dynamic Programming for Two-Player Zero-Sum Markov Games , 2015, ICML.
[16] Yoshua Bengio,et al. An Empirical Investigation of Catastrophic Forgeting in Gradient-Based Neural Networks , 2013, ICLR.
[17] Dean Pomerleau,et al. Efficient Training of Artificial Neural Networks for Autonomous Navigation , 1991, Neural Computation.
[18] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[19] Razvan Pascanu,et al. Sim-to-Real Robot Learning from Pixels with Progressive Nets , 2016, CoRL.
[20] R. French. Catastrophic forgetting in connectionist networks , 1999, Trends in Cognitive Sciences.
[21] Girish Chowdhary,et al. Robust Deep Reinforcement Learning with Adversarial Attacks , 2017, AAMAS.
[22] Saber Fallah,et al. End-to-end Reinforcement Learning for Autonomous Longitudinal Control Using Advantage Actor Critic with Temporal Context , 2019, 2019 IEEE Intelligent Transportation Systems Conference (ITSC).
[23] Sergey Levine,et al. Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[24] Henryk Michalewski,et al. Simulation-Based Reinforcement Learning for Real-World Autonomous Driving , 2020, 2020 IEEE International Conference on Robotics and Automation (ICRA).
[25] Derek Hoiem,et al. Learning without Forgetting , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[26] Ali Farhadi,et al. Target-driven visual navigation in indoor scenes using deep reinforcement learning , 2016, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[27] Mykel J. Kochenderfer,et al. Imitating driver behavior with generative adversarial networks , 2017, 2017 IEEE Intelligent Vehicles Symposium (IV).
[28] Silvio Savarese,et al. Adversarially Robust Policy Learning: Active construction of physically-plausible perturbations , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[29] Alexey Dosovitskiy,et al. End-to-End Driving Via Conditional Imitation Learning , 2017, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[30] Jun Morimoto,et al. Robust Reinforcement Learning , 2005, Neural Computation.
[31] Katherine Rose Driggs-Campbell,et al. Improved Robustness and Safety for Autonomous Vehicle Control with Adversarial Reinforcement Learning , 2018, 2018 IEEE Intelligent Vehicles Symposium (IV).
[32] Cewu Lu,et al. Virtual to Real Reinforcement Learning for Autonomous Driving , 2017, BMVC.
[33] Richard Bowden,et al. Safe Deep Neural Network-Driven Autonomous Vehicles Using Software Safety Cages , 2019, IDEAL.
[34] Eder Santana,et al. Exploring the Limitations of Behavior Cloning for Autonomous Driving , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
[35] Joan Bruna,et al. Intriguing properties of neural networks , 2013, ICLR.
[36] Wojciech Zaremba,et al. Domain randomization for transferring deep neural networks from simulation to the real world , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[37] Frank Diermeyer,et al. Survey on Scenario-Based Safety Assessment of Automated Vehicles , 2020, IEEE Access.
[38] Michael L. Littman,et al. Markov Games as a Framework for Multi-Agent Reinforcement Learning , 1994, ICML.
[39] Mykel J. Kochenderfer,et al. A Survey of Algorithms for Black-Box Safety Validation , 2020, J. Artif. Intell. Res..
[40] Jonathon Shlens,et al. Explaining and Harnessing Adversarial Examples , 2014, ICLR.
[41] Wenhao Ding,et al. Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation , 2020, IEEE Robotics and Automation Letters.
[42] Razvan Pascanu,et al. Policy Distillation , 2015, ICLR.
[43] Sergey Levine,et al. Adversarial Policies: Attacking Deep Reinforcement Learning , 2019, ICLR.
[44] Geoffrey J. Gordon,et al. A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning , 2010, AISTATS.
[45] Richard Bowden,et al. A Survey of Deep Learning Applications to Autonomous Vehicle Control , 2019, IEEE Transactions on Intelligent Transportation Systems.
[46] Gregory D. Hager,et al. Uncertainty-Aware Occupancy Map Prediction Using Generative Networks for Robot Navigation , 2019, 2019 International Conference on Robotics and Automation (ICRA).
[47] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[48] Alex Graves,et al. Asynchronous Methods for Deep Reinforcement Learning , 2016, ICML.