Efficiently Guiding Imitation Learning Agents with Human Gaze
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Scott Niekum | Ruohan Zhang | Akanksha Saran | Elaine Schaertl Short | S. Niekum | Akanksha Saran | Ruohan Zhang
[1] Matthew D. Zeiler. ADADELTA: An Adaptive Learning Rate Method , 2012, ArXiv.
[2] Stephen P. Boyd,et al. Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.
[3] Stefano Ermon,et al. Label-Free Supervision of Neural Networks with Physics and Domain Knowledge , 2016, AAAI.
[4] Stuart J. Russell,et al. Inverse reinforcement learning for video games , 2018, ArXiv.
[5] Stefano Ermon,et al. Generative Adversarial Imitation Learning , 2016, NIPS.
[6] Sergey Levine,et al. Learning Robust Rewards with Adversarial Inverse Reinforcement Learning , 2017, ICLR 2017.
[7] Andrea Lockerd Thomaz,et al. Human Gaze Following for Human-Robot Interaction , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[8] Scott Niekum,et al. Understanding Teacher Gaze Patterns for Robot Learning , 2019, CoRL.
[9] Geoffrey J. Gordon,et al. A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning , 2010, AISTATS.
[10] Mark R. Wilson,et al. Cheating experience: Guiding novices to adopt the gaze strategies of experts expedites the learning of technical laparoscopic skills. , 2012, Surgery.
[11] Yusuke Yamani,et al. Following Expert's Eyes: Evaluation of the Effectiveness of a Gaze-Based Training Intervention on Young Drivers' Latent Hazard Anticipation Skills , 2017 .
[12] Bo Liu,et al. Human Gaze Assisted Artificial Intelligence: A Review , 2020, IJCAI.
[13] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[14] Stefano Nolfi,et al. Selective attention enables action selection: evidence from evolutionary robotics experiments , 2013, Adapt. Behav..
[15] Dana H. Ballard,et al. An Initial Attempt of Combining Visual Selective Attention with Deep Reinforcement Learning , 2018, ArXiv.
[16] D. Ballard,et al. Eye movements in natural behavior , 2005, Trends in Cognitive Sciences.
[17] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[18] Tom Schaul,et al. Rainbow: Combining Improvements in Deep Reinforcement Learning , 2017, AAAI.
[19] Jonathan Dodge,et al. Visualizing and Understanding Atari Agents , 2017, ICML.
[20] Sergey Levine,et al. Causal Confusion in Imitation Learning , 2019, NeurIPS.
[21] J. Platt,et al. Constrained Differential Optimization for Neural Networks , 1988 .
[22] Alejandro Bordallo,et al. Physical symbol grounding and instance learning through demonstration and eye tracking , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[23] Xiaodong Gu,et al. Towards dropout training for convolutional neural networks , 2015, Neural Networks.
[24] M. Land. Vision, eye movements, and natural behavior , 2009, Visual Neuroscience.
[25] Abhishek Das,et al. Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[26] Michael C. Yip,et al. Adversarial Imitation via Variational Inverse Reinforcement Learning , 2018, ICLR.
[27] M. Posner,et al. Orienting of Attention* , 1980, The Quarterly journal of experimental psychology.
[28] Demis Hassabis,et al. Mastering the game of Go with deep neural networks and tree search , 2016, Nature.
[29] Marc G. Bellemare,et al. The Arcade Learning Environment: An Evaluation Platform for General Agents , 2012, J. Artif. Intell. Res..
[30] Luxin Zhang,et al. Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset , 2019, ArXiv.
[31] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[32] Mary M Hayhoe,et al. Task and context determine where you look. , 2016, Journal of vision.
[33] Peter Stone,et al. Leveraging Human Guidance for Deep Reinforcement Learning Tasks , 2019, IJCAI.
[34] Sergey Levine,et al. Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization , 2016, ICML.
[35] Ming Liu,et al. Gaze Training by Modulated Dropout Improves Imitation Learning , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[36] Stefan Schaal,et al. Learning from Demonstration , 1996, NIPS.
[37] D. Ballard,et al. Eye guidance in natural vision: reinterpreting salience. , 2011, Journal of vision.
[38] Peter Stone,et al. Behavioral Cloning from Observation , 2018, IJCAI.
[39] Christof Koch,et al. A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .
[40] Martial Hebert,et al. Learning Transferable Policies for Monocular Reactive MAV Control , 2016, ISER.
[41] Nando de Freitas,et al. Playing hard exploration games by watching YouTube , 2018, NeurIPS.
[42] Shane Legg,et al. Reward learning from human preferences and demonstrations in Atari , 2018, NeurIPS.
[43] Alexei A. Efros,et al. Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[44] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[45] Yuval Tassa,et al. MuJoCo: A physics engine for model-based control , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[46] Frédo Durand,et al. What Do Different Evaluation Metrics Tell Us About Saliency Models? , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[47] Thierry Baccino,et al. Methods for comparing scanpaths and saliency maps: strengths and weaknesses , 2012, Behavior Research Methods.
[48] Brett Browning,et al. A survey of robot learning from demonstration , 2009, Robotics Auton. Syst..
[49] Nitish Srivastava,et al. Improving neural networks by preventing co-adaptation of feature detectors , 2012, ArXiv.
[50] Ming Liu,et al. A gaze model improves autonomous driving , 2019, ETRA.
[51] Luxin Zhang,et al. AGIL: Learning Attention from Human for Visuomotor Tasks , 2018, ECCV.
[52] Prabhat Nagarajan,et al. Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations , 2019, ICML.
[53] Gunnar Farnebäck,et al. Two-Frame Motion Estimation Based on Polynomial Expansion , 2003, SCIA.
[54] David Whitney,et al. Periphery-Fovea Multi-Resolution Driving Model Guided by Human Attention , 2019, 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).