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Vijay Kumar | Konstantinos Karydis | Daniel D. Lee | Arbaaz Khan | Clark Zhang | Nikolay Atanasov | Daniel D. Lee | Vijay R. Kumar | Nikolay A. Atanasov | Arbaaz Khan | Clark Zhang | Konstantinos Karydis
[1] Sean R Eddy,et al. What is dynamic programming? , 2004, Nature Biotechnology.
[2] Sergio Gomez Colmenarejo,et al. Hybrid computing using a neural network with dynamic external memory , 2016, Nature.
[3] Vijay Kumar,et al. Neural Network Memory Architectures for Autonomous Robot Navigation , 2017, ArXiv.
[4] Gaurav S. Sukhatme,et al. Self-supervised regrasping using spatio-temporal tactile features and reinforcement learning , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[5] Alex Graves,et al. Playing Atari with Deep Reinforcement Learning , 2013, ArXiv.
[6] Rahul Sukthankar,et al. Cognitive Mapping and Planning for Visual Navigation , 2017, International Journal of Computer Vision.
[7] Sergey Levine,et al. Learning deep control policies for autonomous aerial vehicles with MPC-guided policy search , 2015, 2016 IEEE International Conference on Robotics and Automation (ICRA).
[8] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[9] Luca Maria Gambardella,et al. Human-friendly robot navigation in dynamic environments , 2013, 2013 IEEE International Conference on Robotics and Automation.
[10] Sergey Levine,et al. End-to-End Training of Deep Visuomotor Policies , 2015, J. Mach. Learn. Res..
[11] Jürgen Schmidhuber,et al. A Machine Learning Approach to Visual Perception of Forest Trails for Mobile Robots , 2016, IEEE Robotics and Automation Letters.
[12] Alex Graves,et al. Neural Turing Machines , 2014, ArXiv.
[13] Sergey Levine,et al. Exploring Deep and Recurrent Architectures for Optimal Control , 2013, ArXiv.
[14] Peter Norvig,et al. Artificial Intelligence: A Modern Approach , 1995 .
[15] Sebastian Thrun,et al. ARA*: Anytime A* with Provable Bounds on Sub-Optimality , 2003, NIPS.
[16] Hava T. Siegelmann,et al. On the Computational Power of Neural Nets , 1995, J. Comput. Syst. Sci..
[17] Doina Precup,et al. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning , 1999, Artif. Intell..
[18] Sergey Levine,et al. Learning Visual Servoing with Deep Features and Fitted Q-Iteration , 2017, ICLR.
[19] Martial Hebert,et al. Learning Transferable Policies for Monocular Reactive MAV Control , 2016, ISER.
[20] Pieter Abbeel,et al. Value Iteration Networks , 2016, NIPS.
[21] Alex Graves,et al. Asynchronous Methods for Deep Reinforcement Learning , 2016, ICML.
[22] Wolfram Burgard,et al. Neural SLAM: Learning to Explore with External Memory , 2017, 1706.09520.
[23] Honglak Lee,et al. Control of Memory, Active Perception, and Action in Minecraft , 2016, ICML.
[24] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[25] Marcin Andrychowicz,et al. Neural Random Access Machines , 2015, ERCIM News.
[26] Jason Weston,et al. Curriculum learning , 2009, ICML '09.
[27] Jason Weston,et al. End-To-End Memory Networks , 2015, NIPS.
[28] Ruslan Salakhutdinov,et al. Neural Map: Structured Memory for Deep Reinforcement Learning , 2017, ICLR.
[29] Sebastian Thrun,et al. Simultaneous Localization and Mapping , 2008, Robotics and Cognitive Approaches to Spatial Mapping.
[30] Sergey Levine,et al. Learning deep neural network policies with continuous memory states , 2015, 2016 IEEE International Conference on Robotics and Automation (ICRA).