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2020 – today
- 2023
[c53]Peter Sunehag, Alexander Sasha Vezhnevets, Edgar A. Duéñez-Guzmán, Igor Mordatch, Joel Z. Leibo:
Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition. AAMAS 2023: 2827-2829- [c52]Shuang Li, Yilun Du, Joshua B. Tenenbaum, Antonio Torralba, Igor Mordatch:
Composing Ensembles of Pre-trained Models via Iterative Consensus. ICLR 2023 - [c51]Danny Driess, Fei Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, Wenlong Huang, Yevgen Chebotar, Pierre Sermanet, Daniel Duckworth, Sergey Levine, Vincent Vanhoucke, Karol Hausman, Marc Toussaint, Klaus Greff, Andy Zeng, Igor Mordatch, Pete Florence:
PaLM-E: An Embodied Multimodal Language Model. ICML 2023: 8469-8488 - [c50]David Venuto, Sherry Yang, Pieter Abbeel, Doina Precup, Igor Mordatch, Ofir Nachum:
Multi-Environment Pretraining Enables Transfer to Action Limited Datasets. ICML 2023: 35024-35036 - [c49]Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin, Igor Mordatch, Pieter Abbeel, Aravind Rajeswaran:
Masked Trajectory Models for Prediction, Representation, and Control. ICML 2023: 37607-37623 - [c48]Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Joseph Dabis, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alexander Herzog, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Tomas Jackson, Sally Jesmonth, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Kuang-Huei Lee, Sergey Levine, Yao Lu, Utsav Malla, Deeksha Manjunath, Igor Mordatch, Ofir Nachum, Carolina Parada, Jodilyn Peralta, Emily Perez, Karl Pertsch, Jornell Quiambao, Kanishka Rao, Michael S. Ryoo, Grecia Salazar, Pannag R. Sanketi, Kevin Sayed, Jaspiar Singh, Sumedh Sontakke, Austin Stone, Clayton Tan, Huong T. Tran, Vincent Vanhoucke, Steve Vega, Quan Vuong, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich:
RT-1: Robotics Transformer for Real-World Control at Scale. Robotics: Science and Systems 2023 - [i57]Peter Sunehag, Alexander Sasha Vezhnevets, Edgar A. Duéñez-Guzmán
, Igor Mordatch, Joel Z. Leibo:
Diversity Through Exclusion (DTE): Niche Identification for Reinforcement Learning through Value-Decomposition. CoRR abs/2302.01180 (2023) - [i56]Wenlong Huang, Fei Xia, Dhruv Shah, Danny Driess, Andy Zeng, Yao Lu, Pete Florence, Igor Mordatch, Sergey Levine, Karol Hausman, Brian Ichter:
Grounded Decoding: Guiding Text Generation with Grounded Models for Robot Control. CoRR abs/2303.00855 (2023) - [i55]Danny Driess, Fei Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, Wenlong Huang, Yevgen Chebotar, Pierre Sermanet, Daniel Duckworth, Sergey Levine, Vincent Vanhoucke, Karol Hausman, Marc Toussaint, Klaus Greff, Andy Zeng, Igor Mordatch, Pete Florence:
PaLM-E: An Embodied Multimodal Language Model. CoRR abs/2303.03378 (2023) - [i54]Satoshi Kataoka, Youngseog Chung, Seyed Kamyar Seyed Ghasemipour, Pannag Sanketi, Shixiang Shane Gu, Igor Mordatch:
Bi-Manual Block Assembly via Sim-to-Real Reinforcement Learning. CoRR abs/2303.14870 (2023) - [i53]Philipp Wu, Arjun Majumdar, Kevin Stone, Yixin Lin, Igor Mordatch, Pieter Abbeel, Aravind Rajeswaran:
Masked Trajectory Models for Prediction, Representation, and Control. CoRR abs/2305.02968 (2023) - [i52]Yilun Du, Shuang Li, Antonio Torralba, Joshua B. Tenenbaum, Igor Mordatch:
Improving Factuality and Reasoning in Language Models through Multiagent Debate. CoRR abs/2305.14325 (2023) - [i51]Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Xi Chen, Krzysztof Choromanski, Tianli Ding, Danny Driess, Avinava Dubey, Chelsea Finn, Pete Florence, Chuyuan Fu, Montse Gonzalez Arenas, Keerthana Gopalakrishnan, Kehang Han, Karol Hausman, Alexander Herzog, Jasmine Hsu, Brian Ichter, Alex Irpan, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Lisa Lee, Tsang-Wei Edward Lee, Sergey Levine, Yao Lu, Henryk Michalewski, Igor Mordatch, Karl Pertsch, Kanishka Rao, Krista Reymann, Michael S. Ryoo, Grecia Salazar, Pannag Sanketi, Pierre Sermanet, Jaspiar Singh, Anikait Singh, Radu Soricut, Huong T. Tran, Vincent Vanhoucke, Quan Vuong, Ayzaan Wahid, Stefan Welker, Paul Wohlhart, Jialin Wu, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich:
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control. CoRR abs/2307.15818 (2023) - 2022
- [c47]Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch:
Frozen Pretrained Transformers as Universal Computation Engines. AAAI 2022: 7628-7636 - [c46]Shuang Li, Yilun Du, Gido van de Ven, Igor Mordatch:
Energy-Based Models for Continual Learning. CoLLAs 2022: 1-22 - [c45]Wenlong Huang, Fei Xia, Ted Xiao, Harris Chan, Jacky Liang, Pete Florence, Andy Zeng, Jonathan Tompson, Igor Mordatch, Yevgen Chebotar, Pierre Sermanet, Tomas Jackson, Noah Brown, Linda Luu, Sergey Levine, Karol Hausman, Brian Ichter:
Inner Monologue: Embodied Reasoning through Planning with Language Models. CoRL 2022: 1769-1782 - [c44]Yilun Du, Shuang Li, Joshua B. Tenenbaum, Igor Mordatch:
Learning Iterative Reasoning through Energy Minimization. ICML 2022: 5570-5582 - [c43]Seyed Kamyar Seyed Ghasemipour, Satoshi Kataoka, Byron David, Daniel Freeman, Shixiang Shane Gu, Igor Mordatch:
Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning. ICML 2022: 7435-7469 - [c42]Wenlong Huang, Pieter Abbeel, Deepak Pathak, Igor Mordatch:
Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents. ICML 2022: 9118-9147 - [c41]Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang, Lisa Lee, Daniel Freeman, Sergio Guadarrama, Ian Fischer, Winnie Xu, Eric Jang, Henryk Michalewski, Igor Mordatch:
Multi-Game Decision Transformers. NeurIPS 2022 - [c40]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. NeurIPS 2022 - [i50]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) - [i49]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) - [i48]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) - [i47]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) - [i46]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) - [i45]Yilun Du, Shuang Li, Joshua B. Tenenbaum, Igor Mordatch:
Learning Iterative Reasoning through Energy Minimization. CoRR abs/2206.15448 (2022) - [i44]Wenlong Huang, Fei Xia, Ted Xiao, Harris Chan, Jacky Liang, Pete Florence, Andy Zeng, Jonathan Tompson, Igor Mordatch, Yevgen Chebotar, Pierre Sermanet, Noah Brown, Tomas Jackson, Linda Luu, Sergey Levine, Karol Hausman, Brian Ichter:
Inner Monologue: Embodied Reasoning through Planning with Language Models. CoRR abs/2207.05608 (2022) - [i43]Shuang Li, Yilun Du, Joshua B. Tenenbaum, Antonio Torralba, Igor Mordatch:
Composing Ensembles of Pre-trained Models via Iterative Consensus. CoRR abs/2210.11522 (2022) - [i42]Alexandre Piché, Rafael Pardinas, David Vázquez, Igor Mordatch, Chris Pal:
Implicit Offline Reinforcement Learning via Supervised Learning. CoRR abs/2210.12272 (2022) - [i41]Hao Liu, Xinyang Geng, Lisa Lee, Igor Mordatch, Sergey Levine, Sharan Narang, Pieter Abbeel:
FCM: Forgetful Causal Masking Makes Causal Language Models Better Zero-Shot Learners. CoRR abs/2210.13432 (2022) - [i40]Luke Metz, James Harrison, C. Daniel Freeman, Amil Merchant, Lucas Beyer, James Bradbury, Naman Agrawal, Ben Poole, Igor Mordatch, Adam Roberts, Jascha Sohl-Dickstein:
VeLO: Training Versatile Learned Optimizers by Scaling Up. CoRR abs/2211.09760 (2022) - [i39]David Venuto, Sherry Yang, Pieter Abbeel, Doina Precup, Igor Mordatch, Ofir Nachum:
Multi-Environment Pretraining Enables Transfer to Action Limited Datasets. CoRR abs/2211.13337 (2022) - [i38]John P. Agapiou, Alexander Sasha Vezhnevets, Edgar A. Duéñez-Guzmán, Jayd Matyas, Yiran Mao, Peter Sunehag, Raphael Köster, Udari Madhushani, Kavya Kopparapu, Ramona Comanescu, DJ Strouse, Michael Bradley Johanson, Sukhdeep Singh, Julia Haas, Igor Mordatch, Dean Mobbs, Joel Z. Leibo:
Melting Pot 2.0. CoRR abs/2211.13746 (2022) - [i37]Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Joseph Dabis, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alexander Herzog, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Tomas Jackson, Sally Jesmonth, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Isabel Leal, Kuang-Huei Lee, Sergey Levine, Yao Lu, Utsav Malla, Deeksha Manjunath, Igor Mordatch, Ofir Nachum, Carolina Parada, Jodilyn Peralta, Emily Perez, Karl Pertsch, Jornell Quiambao, Kanishka Rao, Michael S. Ryoo, Grecia Salazar, Pannag Sanketi, Kevin Sayed, Jaspiar Singh, Sumedh Sontakke, Austin Stone, Clayton Tan, Huong T. Tran, Vincent Vanhoucke, Steve Vega, Quan Vuong, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Tianhe Yu, Brianna Zitkovich:
RT-1: Robotics Transformer for Real-World Control at Scale. CoRR abs/2212.06817 (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