Eugene Vinitsky

Human-compatible driving partners through data-regularized self-play reinforcement learning. D Cornelisse, E Vinitsky arXiv preprint arXiv:2403.19648, 2024.

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GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS. S Kazemkhani, A Pandya, D Cornelisse, B Shacklett, E Vinitsky arXiv preprint arXiv:2408.01584, 2024.

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Traffic control via connected and automated vehicles: An open-road field experiment with 100 cavs. JW Lee, H Wang, K Jang, A Hayat, M Bunting, A Alanqary, W Barbour, ... arXiv preprint arXiv:2402.17043, 2024.

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Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test. K Jang, N Lichtle , E Vinitsky, A Shah, M Bunting, M Nice, B Piccoli, ... arXiv preprint arXiv:2402.17050, 2024.

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Traffic smoothing controllers for autonomous vehicles using deep reinforcement learning and real-world trajectory data. N Lichtle , K Jang, A Shah, E Vinitsky, JW Lee, AM Bayen 2023 IEEE 26th International Conference on Intelligent Transportation ..., 2023.

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Optimizing mixed autonomy traffic flow with decentralized autonomous vehicles and multi-agent reinforcement learning. E Vinitsky, N Lichtle , K Parvate, A Bayen ACM Transactions on Cyber-Physical Systems 7 (2), 1-22, 2023.

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Stabilizing unsupervised environment design with a learned adversary. I Mediratta, M Jiang, J Parker-Holder, M Dennis, E Vinitsky, T Rockta schel Conference on Lifelong Learning Agents, 270-291, 2023.

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A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings. E Vinitsky, R Ko ster, JP Agapiou, EA Due n ez-Guzma n, AS Vezhnevets, ... Collective Intelligence 2 (2), 26339137231162025, 2023.

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Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world. E Vinitsky, N Lichtle , X Yang, B Amos, J Foerster Advances in Neural Information Processing Systems 35, 3962-3974, 2022.

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Unified automatic control of vehicular systems with reinforcement learning. Z Yan, AR Kreidieh, E Vinitsky, AM Bayen, C Wu IEEE Transactions on Automation Science and Engineering 20 (2), 789-804, 2022.

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From sim-to-real: learning and deploying autonomous vehicle controllers that improve transportation metrics. EA Vinitsky UC Berkeley, 2022.

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On the approximability of time disjoint walks. A Bayen, J Goodman, E Vinitsky Journal of Combinatorial Optimization 44 (3), 1615-1636, 2022.

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Deploying traffic smoothing cruise controllers learned from trajectory data. N Lichtle , E Vinitsky, M Nice, B Seibold, D Work, AM Bayen 2022 International Conference on Robotics and Automation (ICRA), 2884-2890, 2022.

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The surprising effectiveness of ppo in cooperative multi-agent games. C Yu, A Velu, E Vinitsky, J Gao, Y Wang, A Bayen, Y Wu Advances in Neural Information Processing Systems 35, 24611-24624, 2022.

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Integrated framework of vehicle dynamics, instabilities, energy models, and sparse flow smoothing controllers. JW Lee, G Gunter, R Ramadan, S Almatrudi, P Arnold, J Aquino, ... Proceedings of the Workshop on Data-Driven and Intelligent Cyber-Physical ..., 2021.

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The i-24 trajectory dataset. M Nice, N Lichtle, G Gumm, M Roman, E Vinitsky, S Elmadani, M Bunting, ... Vanderbilt Univ., Nashville, TN (United States); University of California ..., 2021.

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Flow: A modular learning framework for mixed autonomy traffic. C Wu, AR Kreidieh, K Parvate, E Vinitsky, AM Bayen IEEE Transactions on Robotics 38 (2), 1270-1286, 2021.

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Fuel consumption reduction of multi-lane road networks using decentralized mixed-autonomy control. N Lichtle , E Vinitsky, G Gunter, A Velu, AM Bayen 2021 IEEE International Intelligent Transportation Systems Conference (ITSC ..., 2021.

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Imitation learning from pixel observations for continuous control. S Cohen, B Amos, MP Deisenroth, M Henaff, E Vinitsky, D Yarats .

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Emergent complexity and zero-shot transfer via unsupervised environment design. M Dennis, N Jaques, E Vinitsky, A Bayen, S Russell, A Critch, S Levine Advances in neural information processing systems 33, 13049-13061, 2020.

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Robust reinforcement learning using adversarial populations. E Vinitsky, Y Du, K Parvate, K Jang, P Abbeel, A Bayen arXiv preprint arXiv:2008.01825, 2020.

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Optimizing mixed autonomy traffic flow with decentralized autonomous vehicles and multi-agent rl. E Vinitsky, N Lichtle, K Parvate, A Bayen arXiv preprint arXiv:2011.00120, 2020.

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Benchmarking multi-agent deep reinforcement learning algorithms. C Yu, A Velu, E Vinitsky, Y Wang, A Bayen, Y Wu .

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Energy Optimization of Traffic at Scale using Reinforcement Learning. E Vinitsky, N Lichtle, A Kriedieh, J Lee, A Velu, S Almatrudi, J Carpio, ... Regents Of The University Of California, The", 2020.

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Zero-shot autonomous vehicle policy transfer: From simulation to real-world via adversarial learning. B Chalaki, LE Beaver, B Remer, K Jang, E Vinitsky, AM Bayen, ... 2020 IEEE 16th international conference on control & automation (ICCA), 35-40, 2020.

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Simulation to scaled city: zero-shot policy transfer for traffic control via autonomous vehicles. K Jang, E Vinitsky, B Chalaki, B Remer, L Beaver, AA Malikopoulos, ... Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical ..., 2019.

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An open source implementation of sequential social dilemma games. E Vinitsky, N Jaques, J Leibo, A Castenada, E Hughes GitHub, 2019.

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Benchmarks for reinforcement learning in mixed-autonomy traffic. E Vinitsky, A Kreidieh, L Le Flem, N Kheterpal, K Jang, C Wu, F Wu, ... Conference on robot learning, 399-409, 2018.

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Lagrangian control through deep-rl: Applications to bottleneck decongestion. E Vinitsky, K Parvate, A Kreidieh, C Wu, A Bayen 2018 21st International Conference on Intelligent Transportation Systems ..., 2018.

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Flow: Deep reinforcement learning for control in sumo. N Kheterpal, K Parvate, C Wu, A Kreidieh, E Vinitsky, A Bayen EPiC Series in Engineering 2, 134-151, 2018.

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Flow: Open source reinforcement learning for traffic control. N Kheterpal, E Vinitsky, C Wu, A Kreidieh, K Jang, K Parvate, A Bayen .

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Flow: Architecture and benchmarking for reinforcement learning in traffic control. C Wu, A Kreidieh, K Parvate, E Vinitsky, AM Bayen arXiv preprint arXiv:1710.05465 10, 2017.

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Emergent behaviors in mixed-autonomy traffic. C Wu, A Kreidieh, E Vinitsky, AM Bayen Conference on Robot Learning, 398-407, 2017.

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Framework for control and deep reinforcement learning in traffic. C Wu, K Parvate, N Kheterpal, L Dickstein, A Mehta, E Vinitsky, AM Bayen 2017 IEEE 20th International Conference on Intelligent Transportation ..., 2017.

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Multi-lane reduction: A stochastic single-lane model for lane changing. C Wu, E Vinitsky, A Kreidieh, A Bayen 2017 IEEE 20th International Conference on Intelligent Transportation ..., 2017.

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Flow: A modular learning framework for autonomy in traffic. C Wu, A Kreidieh, K Parvate, E Vinitsky, AM Bayen arXiv preprint arXiv:1710.05465, 2017.

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Structural, vibrational, and electronic properties of BaReH9 under pressure. EA Vinitsky, T Muramatsu, M Somayazulu, WK Wanene, Z Liu, D Chandra, ... Journal of Physics: Condensed Matter 28 (50), 505701, 2016.

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Metallization and Superconductivity in the Hydrogen-Rich Ionic Salt BaReH9. T Muramatsu, WK Wanene, M Somayazulu, E Vinitsky, D Chandra, ... The Journal of Physical Chemistry C 119 (32), 18007-18013, 2015.

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Particle dynamics in damped nonlinear quadrupole ion traps. EA Vinitsky, ED Black, KG Libbrecht American Journal of Physics 83 (4), 313-319, 2015.

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Extracting Traffic Smoothing Controllers Directly From Driving Data using Offline RL. T Ardoin, ENS Paris-Saclay, E Vinitsky, A Bayen .

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Automatic Curriculum Generation and Emergent Complexity via Inter-agent Competition. E Vinitsky, BA Fickinger, BN Jaques, I Mordatch .

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The surprising effectiveness of ppo in cooperative, multi-agent games. arXiv 2021. C Yu, A Velu, E Vinitsky, Y Wang, A Bayen, Y Wu arXiv preprint arXiv:2103.01955, 0.

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