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Centralized Model and Exploration Policy for Multi-Agent RL


Jul 14, 2021
Qizhen Zhang, Chris Lu, Animesh Garg, Jakob Foerster


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A Persistent Spatial Semantic Representation for High-level Natural Language Instruction Execution


Jul 12, 2021
Valts Blukis, Chris Paxton, Dieter Fox, Animesh Garg, Yoav Artzi

* Submitted to CoRL 2021 

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Learning Latent Actions to Control Assistive Robots


Jul 10, 2021
Dylan P. Losey, Hong Jun Jeon, Mengxi Li, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Jeannette Bohg, Dorsa Sadigh


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GIFT: Generalizable Interaction-aware Functional Tool Affordances without Labels


Jun 28, 2021
Dylan Turpin, Liquan Wang, Stavros Tsogkas, Sven Dickinson, Animesh Garg

* Qualitative results available at https://www.pair.toronto.edu/gift-tools-rss21 

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Neural Hybrid Automata: Learning Dynamics with Multiple Modes and Stochastic Transitions


Jun 08, 2021
Michael Poli, Stefano Massaroli, Luca Scimeca, Seong Joon Oh, Sanghyuk Chun, Atsushi Yamashita, Hajime Asama, Jinkyoo Park, Animesh Garg


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Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning


May 31, 2021
Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar

* 38th International Conference on Machine Learning, PMLR 139, 2021 

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DiSECt: A Differentiable Simulation Engine for Autonomous Robotic Cutting


May 25, 2021
Eric Heiden, Miles Macklin, Yashraj Narang, Dieter Fox, Animesh Garg, Fabio Ramos

* Accepted at Robotics: Science and Systems 2021 

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Robust Value Iteration for Continuous Control Tasks


May 25, 2021
Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg

* Accepted Paper at Robotics: Science and Systems 

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Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition


May 18, 2021
Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, Animashree Anandkumar


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Principled Exploration via Optimistic Bootstrapping and Backward Induction


May 17, 2021
Chenjia Bai, Lingxiao Wang, Lei Han, Jianye Hao, Animesh Garg, Peng Liu, Zhaoran Wang

* ICML 2021 

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Value Iteration in Continuous Actions, States and Time


May 10, 2021
Michael Lutter, Shie Mannor, Jan Peters, Dieter Fox, Animesh Garg

* Accepted at International Conference on Machine Learning (ICML) 2021 

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GLiDE: Generalizable Quadrupedal Locomotion in Diverse Environments with a Centroidal Model


Apr 22, 2021
Zhaoming Xie, Xingye Da, Buck Babich, Animesh Garg, Michiel van de Panne


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LASER: Learning a Latent Action Space for Efficient Reinforcement Learning


Mar 30, 2021
Arthur Allshire, Roberto Martín-Martín, Charles Lin, Shawn Manuel, Silvio Savarese, Animesh Garg

* Accepted as a conference paper at ICRA 2021. 7 pages, 8 figures 

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Articulated Object Interaction in Unknown Scenes with Whole-Body Mobile Manipulation


Mar 18, 2021
Mayank Mittal, David Hoeller, Farbod Farshidian, Marco Hutter, Animesh Garg


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S4RL: Surprisingly Simple Self-Supervision for Offline Reinforcement Learning


Mar 10, 2021
Samarth Sinha, Animesh Garg


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Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos


Jan 18, 2021
Haoyu Xiong, Quanzhou Li, Yun-Chun Chen, Homanga Bharadhwaj, Samarth Sinha, Animesh Garg

* Project Website: https://www.pair.toronto.edu/lbw-kp/ 

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Emergent Hand Morphology and Control from Optimizing Robust Grasps of Diverse Objects


Dec 22, 2020
Xinlei Pan, Animesh Garg, Animashree Anandkumar, Yuke Zhu

* 8 pages, 5 figures, Project website: https://xinleipan.github.io/emergent_morphology/ 

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C-Learning: Horizon-Aware Cumulative Accessibility Estimation


Dec 14, 2020
Panteha Naderian, Gabriel Loaiza-Ganem, Harry J. Braviner, Anthony L. Caterini, Jesse C. Cresswell, Tong Li, Animesh Garg


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Skill Transfer via Partially Amortized Hierarchical Planning


Nov 27, 2020
Kevin Xie, Homanga Bharadhwaj, Danijar Hafner, Animesh Garg, Florian Shkurti

* First two authors contributed equally. Preprint. NeurIPS 2020 Deep RL Workshop and under review 

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Action Concept Grounding Network for Semantically-Consistent Video Generation


Nov 23, 2020
Wei Yu, Wenxin Chen, Steve Easterbrook, Animesh Garg


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Solving Physics Puzzles by Reasoning about Paths


Nov 14, 2020
Augustin Harter, Andrew Melnik, Gaurav Kumar, Dhruv Agarwal, Animesh Garg, Helge Ritter

* 1st NeurIPS workshop on Interpretable Inductive Biases and Physically Structured Learning (2020) 

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Dynamics Randomization Revisited:A Case Study for Quadrupedal Locomotion


Nov 04, 2020
Zhaoming Xie, Xingye Da, Michiel van de Panne, Buck Babich, Animesh Garg


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Conservative Safety Critics for Exploration


Oct 27, 2020
Homanga Bharadhwaj, Aviral Kumar, Nicholas Rhinehart, Sergey Levine, Florian Shkurti, Animesh Garg

* Preprint. Under review 

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D2RL: Deep Dense Architectures in Reinforcement Learning


Oct 19, 2020
Samarth Sinha, Homanga Bharadhwaj, Aravind Srinivas, Animesh Garg


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Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion


Oct 05, 2020
Xingye Da, Zhaoming Xie, David Hoeller, Byron Boots, Animashree Anandkumar, Yuke Zhu, Buck Babich, Animesh Garg

* supplementary video: https://youtu.be/JJOmFZKpYTo 

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