Eugene Vinitsky
Eugene Vinitsky
Assistant Professor, NYU
Verified email at - Homepage
Cited by
Cited by
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
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
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
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
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
Emergent behaviors in mixed-autonomy traffic
C Wu, A Kreidieh, E Vinitsky, AM Bayen
Conference on Robot Learning, 398-407, 2017
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
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
Robust reinforcement learning using adversarial populations
E Vinitsky, Y Du, K Parvate, K Jang, P Abbeel, A Bayen
arXiv preprint arXiv:2008.01825, 2020
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
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
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
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
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
A learning agent that acquires social norms from public sanctions in decentralized multi-agent settings
E Vinitsky, R Köster, JP Agapiou, EA Duéñez-Guzmán, AS Vezhnevets, ...
Collective Intelligence 2 (2), 26339137231162025, 2023
Deploying traffic smoothing cruise controllers learned from trajectory data
N Lichtlé, E Vinitsky, M Nice, B Seibold, D Work, AM Bayen
2022 International Conference on Robotics and Automation (ICRA), 2884-2890, 2022
Particle dynamics in damped nonlinear quadrupole ion traps
EA Vinitsky, ED Black, KG Libbrecht
American Journal of Physics 83 (4), 313-319, 2015
Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world
E Vinitsky, N Lichtlé, X Yang, B Amos, J Foerster
Advances in Neural Information Processing Systems 35, 3962-3974, 2022
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
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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