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<title>CS391R: Robot Learning</title>
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<h2>Syllabus</h2>
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<h4>Schedule</h4>
<i>All deadlines are 9:59pm CT. Paper reviews are due by the previous night of the presentation date.</i><br>Readings: ● required ■ required (no review) ○ optional
<br><br>
<!-- <h6>Note: The reading list is subject to change prior to the start of the course.</h6> -->
<div class="row" style="margin-top:20px;">
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<table class="table" id="schedule">
<tr class="schedule-header">
<th>Date</th><th>Topic</th><th>Presenters</th><th>Notes</th>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 1</strong><br>Thu, Aug 27</td>
<td class="topic-cell"><p><span class="label label-lecture text-base">Lecture</span> Introduction: Towards General-Purpose Robot Autonomy</p>
<ul class="optional-reading">
<li class="no-review"><a href="https://arxiv.org/abs/1604.00289">Building Machines That Learn and Think Like People</a>. Brenden M. Lake, Tomer D. Ullman, Joshua B. Tenenbaum, Samuel J. Gershman (2016)</li>
<li><a href="https://people.csail.mit.edu/brooks/papers/AIM-1293.pdf">Intelligence without Reason</a>. Rodney Brooks (1991)</li>
</ul>
</td>
<td class="presenters-cell"></td>
<td class="notes-cell"><a href="slides/lecture_intro.pdf">[slides]</a></td>
</tr>
<tr class="schedule-row chapter-row">
<td class="date-cell" colspan="5"><strong>Part I: Robot Perception</strong></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 2</strong><br>Tue, Sept 1</td>
<td class="topic-cell"><p><span class="label label-lecture text-base">Lecture</span> Overview of Robot Perception</p>
<ul class="optional-reading">
<li class="no-review"><a href="https://arxiv.org/abs/1804.06557">The Limits and Potentials of Deep Learning for Robotics</a>. Niko Sünderhauf, Oliver Brock, Walter Scheirer, Raia Hadsell, Dieter Fox, Jürgen Leitner, Ben Upcroft, Pieter Abbeel, Wolfram Burgard, Michael Milford, Peter Corke (2018)</li>
<li><a href="https://www.ncbi.nlm.nih.gov/pubmed/12239892">A Sensorimotor Account of Vision and Visual Consciousness</a>. Kevin O'Regan and Alva Noë (2001)</li>
</ul>
</td>
<td class="presenters-cell"></td>
<td class="notes-cell"><a href="slides/lecture_robot_perception.pdf">[slides]</a></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 2</strong><br>Thu, Sept 3</td>
<td class="topic-cell"><p>Object Detection</p>
<ul>
<li><a href="https://arxiv.org/abs/1703.06870">Mask R-CNN</a>. Kaiming He, Georgia Gkioxari, Piotr Dollar, Ross Girshick (2017)</li>
<li><a href="https://arxiv.org/abs/1506.02640">You Only Look Once: Unified, Real-Time Object Detection</a>. Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi (2015)</li>
</ul>
<ul class="optional-reading">
<li><a href="https://arxiv.org/abs/1506.01497">Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks</a>. Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun (2015)</li>
<li><a href="https://arxiv.org/abs/1808.01244">CornerNet: Detecting Objects as Paired Keypoints</a>. Hei Law, Jia Deng (2018)</li>
</ul>
</td>
<td class="presenters-cell">Tianwei<br>Yue</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 3</strong><br>Tue, Sept 8</td>
<td class="topic-cell"><p>3D Data Processing</p>
<ul>
<li><a href="https://arxiv.org/abs/1706.02413">PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space</a>. Charles R. Qi, Li Yi, Hao Su, Leonidas J. Guibas (2017)</li>
<li><a href="https://arxiv.org/abs/1801.07829">Dynamic Graph CNN for Learning on Point Clouds</a>. Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, Justin M. Solomon (2018)</li>
</ul>
<ul class="optional-reading">
<li><a href="https://arxiv.org/abs/1801.07791">PointCNN: Convolution On X-Transformed Points</a>. Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, Baoquan Chen (2018)</li>
<li><a href="https://arxiv.org/abs/1904.08755">4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks</a>. Christopher Choy, JunYoung Gwak, Silvio Savarese (2019)</li>
</ul>
</td>
<td class="presenters-cell">Bo<br>Yan</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 3</strong><br>Wed, Sept 9</td>
<td class="topic-cell"><p><span class="label label-tutorial text-base">Tutorial</span> Tutorial on physical simulations for robot learning</p>
</td>
<td class="presenters-cell"></td>
<td class="notes-cell"><a href="slides/tutorial_robotics_simulation.pdf">[slides]</a></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 3</strong><br>Thu, Sept 10</td>
<td class="topic-cell"><p>Representation Learning I: Priors</p>
<ul>
<li><a href="https://arxiv.org/abs/1911.12247">Contrastive Learning of Structured World Models</a>. Thomas Kipf, Elise van der Pol, Max Welling (2019)</li>
<li><a href="https://arxiv.org/abs/2006.09661">
Implicit Neural Representations with Periodic Activation Functions</a>. Vincent Sitzmann, Julien N. P. Martel, Alexander W. Bergman, David B. Lindell, Gordon Wetzstein (2020)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://arxiv.org/abs/1911.05722">Momentum Contrast for Unsupervised Visual Representation Learning</a>. Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, Ross Girshick (2019)</li>
<li><a href="https://arxiv.org/abs/1901.05103">DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation</a>. Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, Steven Lovegrove (2019)</li>
</ul>
</td>
<td class="presenters-cell">Tongrui<br>Jang Hyun</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 4</strong><br>Tue, Sept 15</td>
<td class="topic-cell"><p>Representation Learning II: Motions</p>
<ul>
<li><a href="https://arxiv.org/abs/1806.08756">Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulation</a>. Peter R. Florence, Lucas Manuelli, Russ Tedrake (2018)</li>
<li><a href="https://arxiv.org/abs/1906.11883">Unsupervised Learning of Object Keypoints for Perception and Control</a>. Tejas Kulkarni, Ankush Gupta, Catalin Ionescu, Sebastian Borgeaud, Malcolm Reynolds, Andrew Zisserman, Volodymyr Mnih (2019)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://arxiv.org/abs/1612.06370">Learning Features by Watching Objects Move</a>. Deepak Pathak, Ross Girshick, Piotr Dollar, Trevor Darrell, Bharath Hariharan (2016)</li>
<li><a href="https://arxiv.org/abs/1704.06888">Time-Contrastive Networks: Self-Supervised Learning from Video</a>. Pierre Sermanet, Corey Lynch, Yevgen Chebotar, Jasmine Hsu, Eric Jang, Stefan Schaal, Sergey Levine (2017)</li>
</ul>
</td>
<td class="presenters-cell">Mofei<br>Jeffrey</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 4</strong><br>Thu, Sept 17</td>
<td class="topic-cell"><p>Multimodal Perception</p>
<ul>
<li><a href="https://arxiv.org/abs/1810.10191">Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks</a>. Michelle A. Lee, Yuke Zhu, Krishnan Srinivasan, Parth Shah, Silvio Savarese, Li Fei-Fei, Animesh Garg, Jeannette Bohg (2018)</li>
<li><a href="https://arxiv.org/abs/1912.11474">Audio-Visual Embodied Navigation</a>. Changan Chen, Unnat Jain, Carl Schissler, Sebastia Vicenc Amengual Gari, Ziad Al-Halah, Vamsi Krishna Ithapu, Philip Robinson, Kristen Grauman (2020)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://arxiv.org/pdf/1805.11085">More Than a Feeling: Learning to Grasp and Regrasp Using Vision and Touch</a>. Roberto Calandra, Andrew Owens, Dinesh Jayaraman, Justin Lin, Wenzhen Yuan, Jitendra Malik, Edward H. Adelson, Sergey Levine (2018)</li>
<li><a href="https://arxiv.org/abs/1509.07831">Deep Multimodal Embedding: Manipulating Novel Objects with Point-clouds, Language and Trajectories</a>. Jaeyong Sung, Ian Lenz, Ashutosh Saxena (2015)</li>
</ul>
</td>
<td class="presenters-cell">Farzan<br>Changan</td>
<td class="notes-cell">Project Proposal Due</td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 5</strong><br>Tue, Sept 22</td>
<td class="topic-cell"><p>Recursive State Estimation</p>
<ul>
<li><a href="https://arxiv.org/abs/1805.11122">Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors</a>. Rico Jonschkowski, Divyam Rastogi, Oliver Brock (2018)</li>
<li><a href="https://arxiv.org/abs/1805.08975">Particle Filter Networks with Application to Visual Localization</a>. Peter Karkus, David Hsu, Wee Sun Lee (2018)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://arxiv.org/abs/1905.11602">Differentiable Algorithm Networks for Composable Robot Learning</a>. Peter Karkus, Xiao Ma, David Hsu, Leslie Pack Kaelbling, Wee Sun Lee, Tomas Lozano-Perez (2019)</li>
<li><a href="https://arxiv.org/abs/1605.07148">Backprop KF: Learning Discriminative Deterministic State Estimators</a>. Tuomas Haarnoja, Anurag Ajay, Sergey Levine, Pieter Abbeel (2016)</li>
</ul>
</td>
<td class="presenters-cell">Jiaru<br>Haresh</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 5</strong><br>Thu, Sept 24</td>
<td class="topic-cell"><p>Pose Estimation</p>
<ul>
<li><a href="https://arxiv.org/abs/1711.00199">PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes</a>. Yu Xiang, Tanner Schmidt, Venkatraman Narayanan, Dieter Fox (2017)</li>
<li><a href="https://arxiv.org/abs/1901.02970">Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation</a>. He Wang, Srinath Sridhar, Jingwei Huang, Julien Valentin, Shuran Song, Leonidas J. Guibas (2019)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://arxiv.org/abs/1902.01275">Implicit 3D Orientation Learning for 6D Object Detection from RGB Images</a>. Martin Sundermeyer, Zoltan-Csaba Marton, Maximilian Durner, Manuel Brucker, Rudolph Triebel (2019)</li>
<li><a href="https://arxiv.org/abs/1901.04780">DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion</a>. Chen Wang, Danfei Xu, Yuke Zhu, Roberto Martín-Martín, Cewu Lu, Li Fei-Fei, Silvio Savarese (2019)</li>
</ul>
</td>
<td class="presenters-cell">Shailesh<br>Zihang</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 6</strong><br>Mon, Sept 28</td>
<td class="topic-cell"><p><span class="label label-tutorial text-base">Tutorial</span> Tutorial on the PyTorch deep learning framework</p>
</td>
<td class="presenters-cell"></td>
<td class="notes-cell"><a href="slides/tutorial_pytorch_library.pdf">[slides]</a></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 6</strong><br>Tue, Sept 29</td>
<td class="topic-cell"><p>Visual Tracking</p>
<ul>
<li><a href="http://www.roboticsproceedings.org/rss10/p30.pdf">DART: Dense Articulated Real-Time Tracking</a>. Tanner Schmidt, Richard Newcombe, Dieter Fox (2015)</li>
<li><a href="https://arxiv.org/abs/1606.09549">Fully-Convolutional Siamese Networks for Object Tracking</a>. Luca Bertinetto, Jack Valmadre, João F. Henriques, Andrea Vedaldi, Philip H. S. Torr (2016)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://arxiv.org/abs/1812.05050">Fast Online Object Tracking and Segmentation: A Unifying Approach</a>. Qiang Wang, Li Zhang, Luca Bertinetto, Weiming Hu, Philip H.S. Torr (2018)</li>
<li><a href="https://arxiv.org/abs/1604.01802">Learning to Track at 100 FPS with Deep Regression Networks</a>. David Held, Sebastian Thrun, Silvio Savarese (2016)</li>
</ul>
</td>
<td class="presenters-cell">Sung Yeon<br>Shivam</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 6</strong><br>Thu, Oct 1</td>
<td class="topic-cell"><p>Active Perception</p>
<ul>
<li><a href="https://arxiv.org/abs/1709.00507">Learning to Look Around: Intelligently Exploring Unseen Environments for Unknown Tasks</a>. Dinesh Jayaraman, Kristen Grauman (2017)</li>
<li><a href="https://arxiv.org/abs/1606.07419">Learning to Poke by Poking: Experiential Learning of Intuitive Physics</a>. Pulkit Agrawal, Ashvin Nair, Pieter Abbeel, Jitendra Malik, Sergey Levine (2016)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://arxiv.org/abs/1604.03670">Interactive Perception: Leveraging Action in Perception and Perception in Action</a>. Jeannette Bohg, Karol Hausman, Bharath Sankaran, Oliver Brock, Danica Kragic, Stefan Schaal, Gaurav Sukhatme (2016)</li>
<li><a href="https://arxiv.org/abs/1604.01360">The Curious Robot: Learning Visual Representations via Physical Interactions</a>. Lerrel Pinto, Dhiraj Gandhi, Yuanfeng Han, Yong-Lae Park, Abhinav Gupta (2016)</li>
</ul>
</td>
<td class="presenters-cell">Sagnik<br>Jerry</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row chapter-row">
<td class="date-cell" colspan="5" style="text-align:center;"><strong>Part II: Robot Decision Making</strong></td>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 7</strong><br>Tue, Oct 6</td>
<td class="topic-cell"><p><span class="label label-lecture text-base">Lecture</span> Overview of Robot Decision Making</p>
<ul class=optional-reading>
<li class="no-review"><a href="https://www.ias.informatik.tu-darmstadt.de/uploads/Publications/Kober_IJRR_2013.pdf">Reinforcement Learning in Robotics: A Survey</a>. Jens Kober, J. Andrew Bagnell, Jan Peters (2013)</li>
<li><a href="http://lasa.epfl.ch/publications/uploadedFiles/annurev-control-100819-063206.pdf">Recent Advances in Robot Learning from Demonstration</a>. Harish Ravichandar, Athanasios S. Polydoros, Sonia Chernova, Aude Billard (2020)</li>
</ul>
</td>
<td class="presenters-cell"></td>
<td class="notes-cell"><a href="slides/lecture_decision_making.pdf">[slides]</a></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 7</strong><br>Thu, Oct 8</td>
<td class="topic-cell"><p>Model-free Reinforcement Learning</p>
<ul>
<li><a href="https://arxiv.org/abs/1502.05477">Trust Region Policy Optimization</a>. John Schulman, Sergey Levine, Philipp Moritz, Michael I. Jordan, Pieter Abbeel (2015)</li>
<li><a href="https://arxiv.org/abs/1812.05905">Soft Actor-Critic Algorithms and Applications</a>. Tuomas Haarnoja, Aurick Zhou, Kristian Hartikainen, George Tucker, Sehoon Ha, Jie Tan, Vikash Kumar, Henry Zhu, Abhishek Gupta, Pieter Abbeel, Sergey Levine (2018)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://arxiv.org/abs/1509.02971">Continuous Control with Deep Reinforcement Learning</a>. Timothy P. Lillicrap, Jonathan J. Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, Daan Wierstra (2015)</li>
<li><a href="https://arxiv.org/abs/1707.06347">Proximal Policy Optimization Algorithms</a>. John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, Oleg Klimov (2017)</li>
</ul>
</td>
<td class="presenters-cell">Dian<br>Jiaxun</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 8</strong><br>Tue, Oct 13</td>
<td class="topic-cell"><p>Model-based Reinforcement Learning</p>
<ul>
<li><a href="https://rse-lab.cs.washington.edu/papers/robot-rl-rss-11.pdf">Learning to Control a Low-Cost Manipulator using Data-Efficient Reinforcement Learning</a>. Marc Deisenroth, Carl Edward Rasmussen, Dieter Fox (2011)</li>
<li><a href="https://arxiv.org/abs/1912.01603">Dream to Control: Learning Behaviors by Latent Imagination</a>. Danijar Hafner, Timothy Lillicrap, Jimmy Ba, Mohammad Norouzi (2019)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://arxiv.org/abs/1907.02057">Benchmarking Model-Based Reinforcement Learning</a>. Tingwu Wang, Xuchan Bao, Ignasi Clavera, Jerrick Hoang, Yeming Wen, Eric Langlois, Shunshi Zhang, Guodong Zhang, Pieter Abbeel, Jimmy Ba (2017)</li>
<li><a href="https://arxiv.org/abs/1610.00696">Deep Visual Foresight for Planning Robot Motion</a>. Chelsea Finn, Sergey Levine (2016)</li>
</ul>
</td>
<td class="presenters-cell">Adam<br>Priyanka</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 8</strong><br>Thu, Oct 15</td>
<td class="topic-cell"><p>Imitation as Supervised Learning</p>
<ul>
<li><a href="https://arxiv.org/abs/1011.0686">A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning</a>. Stéphane Ross, Geoffrey Gordon, and Drew Bagnell (2010)</li>
<li><a href="https://arxiv.org/abs/1709.07174">Agile Autonomous Driving using End-to-End Deep Imitation Learning</a>. Yunpeng Pan, Ching-An Cheng, Kamil Saigol, Keuntaek Lee, Xinyan Yan, Evangelos A. Theodorou, and Byron Boots (2017)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://arxiv.org/abs/1710.04615">Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation</a>. Tianhao Zhang, Zoe McCarthy, Owen Jow, Dennis Lee, Xi Chen, Ken Goldberg, Pieter Abbeel (2017)</li>
<li><a href="https://arxiv.org/abs/1903.01973">Learning Latent Plans from Play</a>. Corey Lynch, Mohi Khansari, Ted Xiao, Vikash Kumar, Jonathan Tompson, Sergey Levine, Pierre Sermanet (2019)</li>
</ul>
</td>
<td class="presenters-cell">Srinath<br>Satya</td>
<td class="notes-cell">Project Milestone Due</td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 9</strong><br>Tue, Oct 20</td>
<td class="topic-cell"><p>Inverse Reinforcement Learning</p>
<ul>
<li><a href="https://dl.acm.org/doi/10.1145/1015330.1015430">Apprenticeship Learning via Inverse Reinforcement Learning</a>. Pieter Abbeel, Andrew Ng (2004)</li>
<li><a href="https://www.aaai.org/Papers/AAAI/2008/AAAI08-227.pdf">Maximum Entropy Inverse Reinforcement Learning</a>. Brian Ziebart, Andrew Maas, Andrew Bagnell, Anind Dey (2008)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://papers.nips.cc/paper/6420-cooperative-inverse-reinforcement-learning.pdf">Cooperative Inverse Reinforcement Learning</a>. Dylan Hadfield-Menell, Stuart J. Russell, Pieter Abbeel, Anca Dragan (2016)</li>
<li><a href="https://people.eecs.berkeley.edu/~sastry/pubs/Pdfs%20of%202017/SadighActive2017.pdf">Active Preference-Based Learning of Reward Functions</a>. Dorsa Sadigh, Anca Dragan, Shankar Sastry, Sanjit Seshia (2017)</li>
</ul>
</td>
<td class="presenters-cell">Ruohan<br>Yuchen</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 9</strong><br>Thu, Oct 22</td>
<td class="topic-cell"><p>Adversarial Imitation Learning</p>
<ul>
<li><a href="https://arxiv.org/abs/1606.03476">Generative Adversarial Imitation Learning</a>. Jonathan Ho, Stefano Ermon (2016)</li>
<li><a href="https://arxiv.org/abs/1911.02256">A Divergence Minimization Perspective on Imitation Learning Methods</a>. Seyed Kamyar Seyed Ghasemipour, Richard Semel, Shixiang Gu (2019)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://arxiv.org/abs/1703.08840">InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations</a>. Yunzhu Li, Jiaming Song, Stefano Ermon (2017)</li>
<li><a href="https://arxiv.org/abs/1802.09564">Reinforcement and Imitation Learning for Diverse Visuomotor Skills</a>. Yuke Zhu, Ziyu Wang, Josh Merel, Andrei Rusu, Tom Erez, Serkan Cabi, Saran Tunyasuvunakool, János Kramár, Raia Hadsell, Nando de Freitas, Nicolas Heess (2018)</li>
</ul>
</td>
<td class="presenters-cell">Zhendong <br> Yuguang</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row chapter-row">
<td class="date-cell" colspan="5" style="text-align:center;"><strong>Part III: Robots and General Intelligence</strong></td>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 10</strong><br>Tue, Oct 27</td>
<td class="topic-cell"><p>Learning to Learn I: Meta-Learning</p>
<ul>
<li><a href="https://arxiv.org/abs/1703.03400">Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks</a>. Chelsea Finn, Pieter Abbeel, Sergey Levine (2017)</li>
<li><a href="http://proceedings.mlr.press/v48/santoro16.pdf">Meta-Learning with Memory-Augmented Neural Networks</a>. Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, Timothy Lillicrap (2016)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://openreview.net/pdf?id=rJY0-Kcll">Optimization as a Model for Few-Shot Learning</a>. Sachin Ravi, Hugo Larochelle (2017)</li>
<li><a href="https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(19)30061-0">Reinforcement Learning, Fast and Slow</a>. Matthew Botvinick, Sam Ritter, Jane X. Wang, Zeb Kurth-Nelson, Charles Blundell, Demis Hassabis (2019)</li>
</ul>
</td>
<td class="presenters-cell">Caroline <br> Lucas</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 10</strong><br>Thu, Oct 29</td>
<td class="topic-cell"><p>Learning to Learn II: Lifelong Learning</p>
<ul>
<li><a href="https://arxiv.org/abs/1412.0691">RoboBrain: Large-Scale Knowledge Engine for Robots</a>. Ashutosh Saxena, Ashesh Jain, Ozan Sener, Aditya Jami, Dipendra K. Misra, Hema S. Koppula (2014)</li>
<li><a href="https://arxiv.org/abs/1901.01753">Paired Open-Ended Trailblazer (POET): Endlessly Generating Increasingly Complex and Diverse Learning Environments and Their Solutions</a>. Rui Wang, Joel Lehman, Jeff Clune, Kenneth Stanley (2019)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://arxiv.org/abs/1606.09282">Learning without Forgetting</a>. Zhizhong Li, Derek Hoiem (2016)</li>
<li><a href="https://arxiv.org/abs/1604.07255">A Deep Hierarchical Approach to Lifelong Learning in Minecraft</a>. Chen Tessler, Shahar Givony, Tom Zahavy, Daniel J. Mankowitz, Shie Mannor (2016)</li>
</ul>
</td>
<td class="presenters-cell">Maohua <br> Garrett</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 11</strong><br>Tue, Nov 3</td>
<td class="topic-cell"><p>Compositionality I: Hierarchy</p>
<ul>
<li><a href="https://arxiv.org/abs/1604.06057">Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation</a>. Tejas Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Joshua Tenenbaum (2016)</li>
<li><a href="https://arxiv.org/abs/1710.01813">Neural Task Programming: Learning to Generalize Across Hierarchical Tasks</a>. Danfei Xu, Suraj Nair, Yuke Zhu, Julian Gao, Animesh Garg, Li Fei-Fei, Silvio Savarese (2017)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://journals.sagepub.com/doi/abs/10.1177/0278364911428653">Robot Learning from Demonstration by Constructing Skill Trees</a>. George Konidaris, Scott Kuindersma, Roderic Grupen, Andrew Barto (2011)</li>
<li><a href="https://arxiv.org/abs/1609.05140">The Option-Critic Architecture</a>. Pierre-Luc Bacon, Jean Harb, Doina Precup (2016)</li>
</ul>
</td>
<td class="presenters-cell">Prakhar <br> Soroush</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 11</strong><br>Thu, Nov 5</td>
<td class="topic-cell"><p>Compositionality II: Task and Motion</p>
<ul>
<li><a href="https://people.csail.mit.edu/lpk/papers/hpnICRA11Final.pdf">Hierarchical Task and Motion Planning in the Now</a>. Leslie Pack Kaelbling, Tomás Lozano-Pérez (2010)</li>
<li><a href="http://www.roboticsproceedings.org/rss14/p44.pdf">Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning</a>. Marc Toussaint, Kelsey Allen, Kevin Smith, Joshua Tenenbaum (2018)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://arxiv.org/abs/1911.04679">Object-Centric Task and Motion Planning in Dynamic Environments</a>. Toki Migimatsu, Jeannette Bohg (2019)</li>
<li><a href="http://www.cs.utexas.edu/users/pstone/Papers/bib2html-links/AAMAS18-yunl.pdf">PETLON: Planning Efficiently for Task-Level-Optimal Navigation</a>. Shih-Yun Lo, Shiqi Zhang, Peter Stone (2018)</li>
</ul>
</td>
<td class="presenters-cell">Oleg<br>Yifeng</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 12</strong><br>Tue, Nov 10</td>
<td class="topic-cell"><p>Causal Reasoning</p>
<ul>
<li><a href="https://arxiv.org/abs/1911.11185">Theory-based Causal Transfer: Integrating Instance-level Induction and Abstract-level Structure Learning</a>. Mark Edmonds, Xiaojian Ma, Siyuan Qi, Yixin Zhu, Hongjing Lu, Song-Chun Zhu (2019)</li>
<li><a href="https://arxiv.org/abs/1807.09341">Learning Plannable Representations with Causal InfoGAN</a>. Thanard Kurutach, Aviv Tamar, Ge Yang, Stuart Russell, Pieter Abbeel (2018)</li>
</ul>
<ul class=optional-reading>
<!-- <li><a href="https://arxiv.org/abs/1910.01751">Causal Induction from Visual Observations for Goal Directed Tasks</a>. Suraj Nair, Yuke Zhu, Silvio Savarese, Li Fei-Fei (2019)</li> -->
<li><a href="https://arxiv.org/abs/1910.01075">Learning Neural Causal Models from Unknown Interventions</a>. Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Chris Pal, Yoshua Bengio (2019)</li>
<li><a href="https://arxiv.org/abs/1412.2309">Visual Causal Feature Learning</a>. Krzysztof Chalupka, Pietro Perona, Frederick Eberhardt (2014)</li>
</ul>
</td>
<td class="presenters-cell">Jordan <br> Hussein</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row chapter-row">
<td class="date-cell" colspan="5" style="text-align:center;"><strong>Part IV: Robots in the Real World</strong></td>
<tr class="schedule-row">
<tr class="schedule-row">
<td class="date-cell"><strong>Week 12</strong><br>Thu, Nov 12</td>
<td class="topic-cell"><p>Simulation-Reality Gap</p>
<ul>
<li><a href="https://arxiv.org/abs/1906.01728">BayesSim: Adaptive Domain Randomization via Probabilistic Inference for Robotics Simulators</a>. Fabio Ramos, Rafael Carvalhaes Possas, Dieter Fox (2019)</li>
<li><a href="https://arxiv.org/abs/1804.09364">Driving Policy Transfer via Modularity and Abstraction</a>. Matthias Müller, Alexey Dosovitskiy, Bernard Ghanem, Vladlen Koltun (2018)</li>
</ul>
<ul class=optional-reading>
<li><a href="http://openaccess.thecvf.com/content_CVPR_2019/papers/James_Sim-To-Real_via_Sim-To-Sim_Data-Efficient_Robotic_Grasping_via_Randomized-To-Canonical_Adaptation_Networks_CVPR_2019_paper.pdf">Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks</a>. Stephen James, Paul Wohlhart, Mrinal Kalakrishnan, Dmitry Kalashnikov, Alex Irpan, Julian Ibarz, Sergey Levine, Raia Hadsell, Konstantinos Bousmalis (2019)</li>
<li><a href="https://arxiv.org/abs/1904.11621">Meta-Sim: Learning to Generate Synthetic Datasets</a>. Amlan Kar, Aayush Prakash, Ming-Yu Liu, Eric Cameracci, Justin Yuan, Matt Rusiniak, David Acuna, Antonio Torralba, Sanja Fidler (2019)</li>
</ul>
</td>
<td class="presenters-cell">Sai Kiran <br> Ziyang</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 13</strong><br>Tue, Nov 17</td>
<td class="topic-cell"><p>Data-driven Grasping</p>
<ul>
<li><a href="https://arxiv.org/abs/1703.09312">Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics</a>. Jeffrey Mahler, Jacky Liang, Sherdil Niyaz, Michael Laskey, Richard Doan, Xinyu Liu, Juan Aparicio Ojea, Ken Goldberg (2017)</li>
<li><a href="https://arxiv.org/abs/1706.04652">Learning a Visuomotor Controller for Real World Robotic Grasping using Simulated Depth Images</a>. Ulrich Viereck, Andreas ten Pas, Kate Saenko, Robert Platt (2017)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://ieeexplore.ieee.org/document/1241860">Automatic Grasp Planning Using Shape Primitives</a>. Andrew Miller, Steffen Knoop, Henrik Christensen, Peter Allen (2003)</li>
<li><a href="https://ieeexplore.ieee.org/document/6672028">Data-Driven Grasp Synthesis - A Survey</a>. Jeannette Bohg, Antonio Morales, Tamim Asfour (2013)</li>
</ul>
</td>
<td class="presenters-cell">Zhenyu <br> Satyam</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 13</strong><br>Thu, Nov 19</td>
<td class="topic-cell"><p>Building Robotic Systems</p>
<ul>
<li><a href="https://arxiv.org/abs/1806.10293">QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation</a>. Dmitry Kalashnikov, Alex Irpan, Peter Pastor, Julian Ibarz, Alexander Herzog, Eric Jang, Deirdre Quillen, Ethan Holly, Mrinal Kalakrishnan, Vincent Vanhoucke, Sergey Levine (2018)</li>
<li><a href="https://robotics.sciencemag.org/content/4/26/eaau5872">Learning Agile and Dynamic Motor Skills for Legged Robots</a>. Jemin Hwangbo, Joonho Lee, Alexey Dosovitskiy, Dario Bellicoso, Vassilios Tsounis, Vladlen Koltun, Marco Hutter (2019)</li>
</ul>
<ul class=optional-reading>
<li><a href="https://arxiv.org/abs/1903.11239">TossingBot: Learning to Throw Arbitrary Objects with Residual Physics</a>. Andy Zeng, Shuran Song, Johnny Lee, Alberto Rodriguez, Thomas Funkhouser (2019)</li>
<li><a href="http://www.roboticsproceedings.org/rss12/p36.pdf">Lessons from the Amazon Picking Challenge: Four Aspects of Building Robotic Systems</a>. Clemens Eppner, Sebastian Höfer, Rico Jonschkowski, Roberto Martíın-Martín, Arne Sieverling, Vincent Wall, Oliver Brock (2016)</li>
</ul>
</td>
<td class="presenters-cell">Mofei<br>Mingyo</td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 14</strong><br>Tue, Nov 24</td>
<td class="topic-cell"><p><span class="label label-lecture text-base">Lecture</span> Conclusion: Open Questions in Robot Learning</p>
<ul class=optional-reading>
<li><a href="https://arxiv.org/abs/1907.03146">A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms</a>. Oliver Kroemer, Scott Niekum, George Konidaris (2019)</li>
</ul>
</td>
<td class="presenters-cell"></td>
<td class="notes-cell"><a href="slides/lecture_conclusion.pdf">[slides]</a></td>
</tr>
<tr class="schedule-row holiday-row">
<td class="date-cell"><strong>Week 14</strong><br>Thu, Nov 26</td>
<td class="topic-cell">No Class - Thanksgiving Holidays</td>
<td class="presenters-cell"></td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 15</strong><br>Tue, Dec 1</td>
<td class="topic-cell"><span class="label label-spotlight text-base">Spotlight</span> Final Project Spotlights I</td>
<td class="presenters-cell"></td>
<td class="notes-cell">Video Due Nov 29</td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 15</strong><br>Thu, Dec 3</td>
<td class="topic-cell"><span class="label label-spotlight text-base">Spotlight</span> Final Project Spotlights II</td>
<td class="presenters-cell"></td>
<td class="notes-cell"></td>
</tr>
<tr class="schedule-row">
<td class="date-cell"><strong>Week 16</strong><br>Fri, Dec 11</td>
<td class="topic-cell">No Class</td>
<td class="presenters-cell"></td>
<td class="notes-cell">Final Report Due</td>
</tr>
</table>
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