| Multi-agent actor-critic for mixed cooperative-competitive environments R Lowe, YI Wu, A Tamar, J Harb, OAI Pieter Abbeel, I Mordatch Advances in neural information processing systems 30, 2017 | 5441 | 2017 |
| Decision transformer: Reinforcement learning via sequence modeling L Chen, K Lu, A Rajeswaran, K Lee, A Grover, M Laskin, P Abbeel, ... Advances in neural information processing systems 34, 15084-15097, 2021 | 1616 | 2021 |
| Palm-e: An embodied multimodal language model D Driess, F Xia, MSM Sajjadi, C Lynch, A Chowdhery, B Ichter, A Wahid, ... arXiv preprint arXiv:2303.03378, 2023 | 1409 | 2023 |
| Language models as zero-shot planners: Extracting actionable knowledge for embodied agents W Huang, P Abbeel, D Pathak, I Mordatch International conference on machine learning, 9118-9147, 2022 | 968 | 2022 |
| Emergent tool use from multi-agent autocurricula B Baker, I Kanitscheider, T Markov, Y Wu, G Powell, B McGrew, ... arXiv preprint arXiv:1909.07528, 2019 | 876 | 2019 |
| Emergence of grounded compositional language in multi-agent populations I Mordatch, P Abbeel Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 804 | 2018 |
| Inner monologue: Embodied reasoning through planning with language models W Huang, F Xia, T Xiao, H Chan, J Liang, P Florence, A Zeng, J Tompson, ... arXiv preprint arXiv:2207.05608, 2022 | 799 | 2022 |
| Rt-1: Robotics transformer for real-world control at scale A Brohan, N Brown, J Carbajal, Y Chebotar, J Dabis, C Finn, ... arXiv preprint arXiv:2212.06817, 2022 | 787 | 2022 |
| Implicit generation and modeling with energy based models Y Du, I Mordatch Advances in Neural Information Processing Systems 32, 2019 | 733 | 2019 |
| Rt-2: Vision-language-action models transfer web knowledge to robotic control A Brohan, N Brown, J Carbajal, Y Chebotar, X Chen, K Choromanski, ... arXiv preprint arXiv:2307.15818, 2023 | 644 | 2023 |
| Learning with opponent-learning awareness JN Foerster, RY Chen, M Al-Shedivat, S Whiteson, P Abbeel, I Mordatch arXiv preprint arXiv:1709.04326, 2017 | 635 | 2017 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... arXiv preprint arXiv:2403.05530, 2024 | 614 | 2024 |
| Discovery of complex behaviors through contact-invariant optimization I Mordatch, E Todorov, Z Popović ACM Transactions on Graphics (ToG) 31 (4), 1-8, 2012 | 594 | 2012 |
| Emergent complexity via multi-agent competition T Bansal, J Pachocki, S Sidor, I Sutskever, I Mordatch arXiv preprint arXiv:1710.03748, 2017 | 492 | 2017 |
| Continuous adaptation via meta-learning in nonstationary and competitive environments M Al-Shedivat, T Bansal, Y Burda, I Sutskever, I Mordatch, P Abbeel arXiv preprint arXiv:1710.03641, 2017 | 430 | 2017 |
| Improving factuality and reasoning in language models through multiagent debate Y Du, S Li, A Torralba, JB Tenenbaum, I Mordatch arXiv preprint arXiv:2305.14325, 2023 | 381 | 2023 |
| Implicit behavioral cloning P Florence, C Lynch, A Zeng, OA Ramirez, A Wahid, L Downs, A Wong, ... Conference on Robot Learning, 158-168, 2022 | 357 | 2022 |
| Feature-based locomotion controllers M De Lasa, I Mordatch, A Hertzmann ACM transactions on graphics (TOG) 29 (4), 1-10, 2010 | 334 | 2010 |
| Frozen pretrained transformers as universal computation engines K Lu, A Grover, P Abbeel, I Mordatch Proceedings of the AAAI conference on artificial intelligence 36 (7), 7628-7636, 2022 | 303 | 2022 |
| Open x-embodiment: Robotic learning datasets and rt-x models A O'Neill, A Rehman, A Gupta, A Maddukuri, A Gupta, A Padalkar, A Lee, ... arXiv preprint arXiv:2310.08864, 2023 | 279 | 2023 |