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2020 – today
- 2022
[i42]Wenlong Huang, Pieter Abbeel, Deepak Pathak, Igor Mordatch:
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents. CoRR abs/2201.07207 (2022)- [i41]Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, Jacob Andreas, Igor Mordatch, Antonio Torralba, Yuke Zhu:
Pre-Trained Language Models for Interactive Decision-Making. CoRR abs/2202.01771 (2022) - [i40]Satoshi Kataoka, Seyed Kamyar Seyed Ghasemipour, C. Daniel Freeman, Igor Mordatch:
Bi-Manual Manipulation and Attachment via Sim-to-Real Reinforcement Learning. CoRR abs/2203.08277 (2022) - [i39]Seyed Kamyar Seyed Ghasemipour, Daniel Freeman, Byron David, Shixiang Gu, Satoshi Kataoka, Igor Mordatch:
Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning. CoRR abs/2203.13733 (2022) - [i38]Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang, Lisa Lee, Daniel Freeman, Winnie Xu, Sergio Guadarrama, Ian Fischer, Eric Jang, Henryk Michalewski, Igor Mordatch:
Multi-Game Decision Transformers. CoRR abs/2205.15241 (2022) - [i37]Yilun Du, Shuang Li, Joshua B. Tenenbaum, Igor Mordatch:
Learning Iterative Reasoning through Energy Minimization. CoRR abs/2206.15448 (2022) - 2021
- [c39]Pete Florence, Corey Lynch, Andy Zeng, Oscar A. Ramirez, Ayzaan Wahid, Laura Downs, Adrian Wong, Johnny Lee, Igor Mordatch, Jonathan Tompson:
Implicit Behavioral Cloning. CoRL 2021: 158-168 - [c38]Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch:
Reset-Free Lifelong Learning with Skill-Space Planning. ICLR 2021 - [c37]Yilun Du, Shuang Li, Joshua B. Tenenbaum, Igor Mordatch:
Improved Contrastive Divergence Training of Energy-Based Models. ICML 2021: 2837-2848 - [c36]Joel Z. Leibo, Edgar A. Duéñez-Guzmán, Alexander Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charlie Beattie, Igor Mordatch, Thore Graepel:
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot. ICML 2021: 6187-6199 - [c35]Oleh Rybkin, Chuning Zhu, Anusha Nagabandi, Kostas Daniilidis, Igor Mordatch, Sergey Levine:
Model-Based Reinforcement Learning via Latent-Space Collocation. ICML 2021: 9190-9201 - [c34]Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch:
Decision Transformer: Reinforcement Learning via Sequence Modeling. NeurIPS 2021: 15084-15097 - [c33]Yilun Du, Shuang Li, Yash Sharma, Josh Tenenbaum, Igor Mordatch:
Unsupervised Learning of Compositional Energy Concepts. NeurIPS 2021: 15608-15620 - [c32]C. Daniel Freeman, Erik Frey, Anton Raichuk, Sertan Girgin, Igor Mordatch, Olivier Bachem:
Brax - A Differentiable Physics Engine for Large Scale Rigid Body Simulation. NeurIPS Datasets and Benchmarks 2021 - [c31]Joseph Suarez, Yilun Du, Clare Zhu, Igor Mordatch, Phillip Isola:
The Neural MMO Platform for Massively Multiagent Research. NeurIPS Datasets and Benchmarks 2021 - [i36]Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch:
Pretrained Transformers as Universal Computation Engines. CoRR abs/2103.05247 (2021) - [i35]Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch:
Decision Transformer: Reinforcement Learning via Sequence Modeling. CoRR abs/2106.01345 (2021) - [i34]Oleh Rybkin, Chuning Zhu, Anusha Nagabandi, Kostas Daniilidis, Igor Mordatch, Sergey Levine:
Model-Based Reinforcement Learning via Latent-Space Collocation. CoRR abs/2106.13229 (2021) - [i33]C. Daniel Freeman, Erik Frey, Anton Raichuk, Sertan Girgin, Igor Mordatch, Olivier Bachem:
Brax - A Differentiable Physics Engine for Large Scale Rigid Body Simulation. CoRR abs/2106.13281 (2021) - [i32]Joel Z. Leibo, Edgar A. Duéñez-Guzmán, Alexander Sasha Vezhnevets, John P. Agapiou, Peter Sunehag, Raphael Koster, Jayd Matyas, Charles Beattie, Igor Mordatch, Thore Graepel:
Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot. CoRR abs/2107.06857 (2021) - [i31]Pete Florence, Corey Lynch, Andy Zeng, Oscar Ramirez, Ayzaan Wahid, Laura Downs, Adrian Wong, Johnny Lee, Igor Mordatch, Jonathan Tompson:
Implicit Behavioral Cloning. CoRR abs/2109.00137 (2021) - [i30]Joseph Suarez, Yilun Du, Clare Zhu, Igor Mordatch, Phillip Isola:
The Neural MMO Platform for Massively Multiagent Research. CoRR abs/2110.07594 (2021) - [i29]Yilun Du, Shuang Li, Yash Sharma, Joshua B. Tenenbaum, Igor Mordatch:
Unsupervised Learning of Compositional Energy Concepts. CoRR abs/2111.03042 (2021) - [i28]Wenlong Huang, Igor Mordatch, Pieter Abbeel, Deepak Pathak:
Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning. CoRR abs/2111.03062 (2021) - 2020
- [c30]Joseph Suarez, Yilun Du, Igor Mordatch, Phillip Isola:
Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks. AAMAS 2020: 2020-2022 - [c29]Bowen Baker, Ingmar Kanitscheider, Todor M. Markov, Yi Wu, Glenn Powell, Bob McGrew, Igor Mordatch:
Emergent Tool Use From Multi-Agent Autocurricula. ICLR 2020 - [c28]Wenlong Huang, Igor Mordatch, Deepak Pathak:
One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control. ICML 2020: 4455-4464 - [c27]Aravind Rajeswaran, Igor Mordatch, Vikash Kumar:
A Game Theoretic Framework for Model Based Reinforcement Learning. ICML 2020: 7953-7963 - [c26]Yilun Du, Shuang Li, Igor Mordatch:
Compositional Visual Generation with Energy Based Models. NeurIPS 2020 - [c25]Michael Janner, Igor Mordatch, Sergey Levine:
Gamma-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction. NeurIPS 2020 - [i27]Joseph Suarez, Yilun Du, Igor Mordatch, Phillip Isola:
Neural MMO v1.3: A Massively Multiagent Game Environment for Training and Evaluating Neural Networks. CoRR abs/2001.12004 (2020) - [i26]Yilun Du, Shuang Li, Igor Mordatch:
Compositional Visual Generation and Inference with Energy Based Models. CoRR abs/2004.06030 (2020) - [i25]Aravind Rajeswaran, Igor Mordatch, Vikash Kumar:
A Game Theoretic Framework for Model Based Reinforcement Learning. CoRR abs/2004.07804 (2020) - [i24]Wenlong Huang, Igor Mordatch, Deepak Pathak:
One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control. CoRR abs/2007.04976 (2020) - [i23]Michael Janner, Igor Mordatch, Sergey Levine:
γ-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction. CoRR abs/2010.14496 (2020) - [i22]Dhruv Batra, Angel X. Chang, Sonia Chernova, Andrew J. Davison, Jia Deng, Vladlen Koltun, Sergey Levine, Jitendra Malik, Igor Mordatch, Roozbeh Mottaghi, Manolis Savva, Hao Su:
Rearrangement: A Challenge for Embodied AI. CoRR abs/2011.01975 (2020) - [i21]Shuang Li, Yilun Du, Gido M. van de Ven, Antonio Torralba, Igor Mordatch:
Energy-Based Models for Continual Learning. CoRR abs/2011.12216 (2020) - [i20]Yilun Du, Shuang Li, Joshua B. Tenenbaum, Igor Mordatch:
Improved Contrastive Divergence Training of Energy Based Models. CoRR abs/2012.01316 (2020) - [i19]Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch:
Reset-Free Lifelong Learning with Skill-Space Planning. CoRR abs/2012.03548 (2020)
2010 – 2019
- 2019
- [c24]Igor Mordatch:
Concept Learning with Energy-Based Models. CogSci 2019: 58-59 - [c23]Yilun Du, Toru Lin, Igor Mordatch:
Model-Based Planning with Energy-Based Models. CoRL 2019: 374-383 - [c22]Orr Krupnik, Igor Mordatch, Aviv Tamar:
Multi-Agent Reinforcement Learning with Multi-Step Generative Models. CoRL 2019: 776-790 - [c21]Ingmar Kanitscheider, Bowen Baker, Todor M. Markov, Igor Mordatch:
Skill emergence and transfer in multi-agent environments. GECCO (Companion) 2019: 55-56 - [c20]Kendall Lowrey, Aravind Rajeswaran, Sham M. Kakade, Emanuel Todorov, Igor Mordatch:
Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control. ICLR (Poster) 2019 - [c19]Yilun Du, Igor Mordatch:
Implicit Generation and Modeling with Energy Based Models. NeurIPS 2019: 3603-3613 - [i18]Orr Krupnik, Igor Mordatch, Aviv Tamar:
Multi Agent Reinforcement Learning with Multi-Step Generative Models. CoRR abs/1901.10251 (2019) - [i17]Joseph Suarez, Yilun Du, Phillip Isola, Igor Mordatch:
Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents. CoRR abs/1903.00784 (2019) - [i16]Yilun Du, Igor Mordatch:
Implicit Generation and Generalization in Energy-Based Models. CoRR abs/1903.08689 (2019) - [i15]Yilun Du, Toru Lin
, Igor Mordatch:
Model Based Planning with Energy Based Models. CoRR abs/1909.06878 (2019) - [i14]Bowen Baker, Ingmar Kanitscheider, Todor M. Markov, Yi Wu, Glenn Powell, Bob McGrew, Igor Mordatch:
Emergent Tool Use From Multi-Agent Autocurricula. CoRR abs/1909.07528 (2019) - [i13]Kevin Lu, Igor Mordatch, Pieter Abbeel:
Adaptive Online Planning for Continual Lifelong Learning. CoRR abs/1912.01188 (2019) - 2018
- [c18]Igor Mordatch, Pieter Abbeel:
Emergence of Grounded Compositional Language in Multi-Agent Populations. AAAI 2018: 1495-1502 - [c17]Jakob N. Foerster, Richard Y. Chen, Maruan Al-Shedivat, Shimon Whiteson, Pieter Abbeel, Igor Mordatch:
Learning with Opponent-Learning Awareness. AAMAS 2018: 122-130 - [c16]Maruan Al-Shedivat, Trapit Bansal, Yura Burda, Ilya Sutskever, Igor Mordatch, Pieter Abbeel:
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments. ICLR 2018 - [c15]Trapit Bansal, Jakub Pachocki, Szymon Sidor, Ilya Sutskever, Igor Mordatch:
Emergent Complexity via Multi-Agent Competition. ICLR (Poster) 2018 - [c14]Igor Mordatch:
Concept Learning with Energy-Based Models. ICLR (Workshop) 2018 - [c13]Cathy Wu, Aravind Rajeswaran, Yan Duan, Vikash Kumar, Alexandre M. Bayen, Sham M. Kakade, Igor Mordatch, Pieter Abbeel:
Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines. ICLR 2018 - [i12]Cathy Wu, Aravind Rajeswaran, Yan Duan, Vikash Kumar, Alexandre M. Bayen, Sham M. Kakade, Igor Mordatch, Pieter Abbeel:
Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines. CoRR abs/1803.07246 (2018) - [i11]Kendall Lowrey, Aravind Rajeswaran, Sham M. Kakade, Emanuel Todorov, Igor Mordatch:
Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control. CoRR abs/1811.01848 (2018) - [i10]Igor Mordatch:
Concept Learning with Energy-Based Models. CoRR abs/1811.02486 (2018) - 2017
- [c12]Nikhil Mishra, Pieter Abbeel, Igor Mordatch:
Prediction and Control with Temporal Segment Models. ICML 2017: 2459-2468 - [c11]Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, Pieter Abbeel, Igor Mordatch:
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. NIPS 2017: 6379-6390 - [i9]Nikhil Mishra, Pieter Abbeel, Igor Mordatch:
Prediction and Control with Temporal Segment Models. CoRR abs/1703.04070 (2017) - [i8]Igor Mordatch, Pieter Abbeel:
Emergence of Grounded Compositional Language in Multi-Agent Populations. CoRR abs/1703.04908 (2017) - [i7]Ryan Lowe, Yi Wu, Aviv Tamar, Jean Harb, Pieter Abbeel, Igor Mordatch:
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. CoRR abs/1706.02275 (2017) - [i6]Jakob N. Foerster, Richard Y. Chen, Maruan Al-Shedivat, Shimon Whiteson, Pieter Abbeel, Igor Mordatch:
Learning with Opponent-Learning Awareness. CoRR abs/1709.04326 (2017) - [i5]Maruan Al-Shedivat, Trapit Bansal, Yuri Burda, Ilya Sutskever, Igor Mordatch, Pieter Abbeel:
Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments. CoRR abs/1710.03641 (2017) - [i4]Trapit Bansal, Jakub Pachocki, Szymon Sidor, Ilya Sutskever, Igor Mordatch:
Emergent Complexity via Multi-Agent Competition. CoRR abs/1710.03748 (2017) - [i3]Smitha Milli, Pieter Abbeel, Igor Mordatch:
Interpretable and Pedagogical Examples. CoRR abs/1711.00694 (2017) - 2016
- [c10]Igor Mordatch, Nikhil Mishra, Clemens Eppner, Pieter Abbeel:
Combining model-based policy search with online model learning for control of physical humanoids. ICRA 2016: 242-248 - [i2]Paul F. Christiano, Zain Shah, Igor Mordatch, Jonas Schneider, Trevor Blackwell, Joshua Tobin, Pieter Abbeel, Wojciech Zaremba:
Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model. CoRR abs/1610.03518 (2016) - [i1]Jon Gauthier, Igor Mordatch:
A Paradigm for Situated and Goal-Driven Language Learning. CoRR abs/1610.03585 (2016) - 2015
- [b1]Igor Mordatch:
Automated Discovery and Learning of Complex Movement Behaviors. University of Washington, USA, 2015 - [c9]Nikita Kitaev, Igor Mordatch, Sachin Patil, Pieter Abbeel:
Physics-based trajectory optimization for grasping in cluttered environments. ICRA 2015: 3102-3109 - [c8]Igor Mordatch, Kendall Lowrey, Emanuel Todorov:
Ensemble-CIO: Full-body dynamic motion planning that transfers to physical humanoids. IROS 2015: 5307-5314 - [c7]Igor Mordatch, Kendall Lowrey, Galen Andrew, Zoran Popovic, Emanuel Todorov:
Interactive Control of Diverse Complex Characters with Neural Networks. NIPS 2015: 3132-3140 - 2014
- [c6]Igor Mordatch, Emo Todorov:
Combining the benefits of function approximation and trajectory optimization. Robotics: Science and Systems 2014 - 2013
- [j5]Pierre Bénard, Forrester Cole, Michael Kass, Igor Mordatch, James Hegarty, Martin Sebastian Senn, Kurt W. Fleischer, Davide Pesare, Katherine Breeden:
Stylizing animation by example. ACM Trans. Graph. 32(4): 119:1-119:12 (2013) - [j4]Igor Mordatch, Jack M. Wang, Emanuel Todorov, Vladlen Koltun:
Animating human lower limbs using contact-invariant optimization. ACM Trans. Graph. 32(6): 203:1-203:8 (2013) - 2012
- [j3]Igor Mordatch, Emanuel Todorov, Zoran Popovic:
Discovery of complex behaviors through contact-invariant optimization. ACM Trans. Graph. 31(4): 43:1-43:8 (2012) - [c5]Igor Mordatch, Zoran Popovic, Emanuel Todorov:
Contact-Invariant Optimization for Hand Manipulation. Symposium on Computer Animation 2012: 137-144 - 2010
- [j2]Igor Mordatch, Martin de Lasa, Aaron Hertzmann:
Robust physics-based locomotion using low-dimensional planning. ACM Trans. Graph. 29(4): 71:1-71:8 (2010) - [j1]Martin de Lasa, Igor Mordatch, Aaron Hertzmann:
Feature-based locomotion controllers. ACM Trans. Graph. 29(4): 131:1-131:10 (2010)
2000 – 2009
- 2009
- [c4]James McCrae, Igor Mordatch, Michael Glueck, Azam Khan:
Multiscale 3D navigation. SI3D 2009: 7-14 - 2008
- [c3]George W. Fitzmaurice, Justin Matejka, Igor Mordatch, Azam Khan, Gordon Kurtenbach:
Safe 3D navigation. SI3D 2008: 7-15 - [c2]Azam Khan, Igor Mordatch, George W. Fitzmaurice, Justin Matejka, Gordon Kurtenbach:
ViewCube: a 3D orientation indicator and controller. SI3D 2008: 17-25 - 2007
- [c1]Igor Mordatch, Patrick Coleman, Karan Singh, Ravin Balakrishnan:
Interface techniques for 3D control of spatial keyframing. SIGGRAPH Posters 2007: 84
Coauthor Index
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