no code implementations • NeurIPS 2015 • Walid Krichene, Alexandre Bayen, Peter L. Bartlett
We study accelerated mirror descent dynamics in continuous and discrete time.
no code implementations • 3 Jun 2016 • Maximilian Balandat, Walid Krichene, Claire Tomlin, Alexandre Bayen
Under the assumption of uniformly continuous rewards, we obtain explicit anytime regret bounds in a setting where the decision set is the set of probability distributions on a compact metric space $S$ whose Radon-Nikodym derivatives are elements of $L^p(S)$ for some $p > 1$.
no code implementations • NeurIPS 2016 • Maximilian Balandat, Walid Krichene, Claire Tomlin, Alexandre Bayen
We study a general adversarial online learning problem, in which we are given a decision set X' in a reflexive Banach space X and a sequence of reward vectors in the dual space of X.
no code implementations • NeurIPS 2016 • Walid Krichene, Alexandre Bayen, Peter L. Bartlett
This dynamics can be described naturally as a coupling of a dual variable accumulating gradients at a given rate $\eta(t)$, and a primal variable obtained as the weighted average of the mirrored dual trajectory, with weights $w(t)$.
1 code implementation • 14 Dec 2018 • Kathy Jang, Eugene Vinitsky, Behdad Chalaki, Ben Remer, Logan Beaver, Andreas Malikopoulos, Alexandre Bayen
We then directly transfer this policy without any tuning to the University of Delaware Scaled Smart City (UDSSC), a 1:25 scale testbed for connected and automated vehicles.
1 code implementation • 4 Aug 2020 • Eugene Vinitsky, Yuqing Du, Kanaad Parvate, Kathy Jang, Pieter Abbeel, Alexandre Bayen
Reinforcement Learning (RL) is an effective tool for controller design but can struggle with issues of robustness, failing catastrophically when the underlying system dynamics are perturbed.
Out-of-Distribution Generalization reinforcement-learning +1
1 code implementation • 30 Oct 2020 • Eugene Vinitsky, Nathan Lichtle, Kanaad Parvate, Alexandre Bayen
We apply multi-agent reinforcement algorithms to this problem and demonstrate that significant improvements in bottleneck throughput, from 20\% at a 5\% penetration rate to 33\% at a 40\% penetration rate, can be achieved.
6 code implementations • NeurIPS 2020 • Michael Dennis, Natasha Jaques, Eugene Vinitsky, Alexandre Bayen, Stuart Russell, Andrew Critch, Sergey Levine
We call our technique Protagonist Antagonist Induced Regret Environment Design (PAIRED).
1 code implementation • 25 Dec 2020 • Victor Chan, Qijian Gan, Alexandre Bayen
We fill this gap by enhancing a deep learning approach, Diffusion Convolutional Recurrent Neural Network, with spatial information generated from signal timing plans at targeted intersections.
no code implementations • 1 Jan 2021 • Chao Yu, Akash Velu, Eugene Vinitsky, Yu Wang, Alexandre Bayen, Yi Wu
We benchmark commonly used multi-agent deep reinforcement learning (MARL) algorithms on a variety of cooperative multi-agent games.
15 code implementations • 2 Mar 2021 • Chao Yu, Akash Velu, Eugene Vinitsky, Jiaxuan Gao, Yu Wang, Alexandre Bayen, Yi Wu
This is often due to the belief that PPO is significantly less sample efficient than off-policy methods in multi-agent systems.
Multi-agent Reinforcement Learning reinforcement-learning +3
no code implementations • 2 Apr 2021 • Saleh Albeaik, Alexandre Bayen, Maria Teresa Chiri, Xiaoqian Gong, Amaury Hayat, Nicolas Kardous, Alexander Keimer, Sean T. McQuade, Benedetto Piccoli, Yiling You
First it is shown that, for a specific class of initial data, the vehicles' velocities become negative or even diverge to $-\infty$ in finite time, both undesirable properties for a car-following model.
no code implementations • 14 Dec 2021 • Fangyu Wu, Guanhua Wang, Siyuan Zhuang, Kehan Wang, Alexander Keimer, Ion Stoica, Alexandre Bayen
The proposed scheme does not require pre-computation and can improve the amortized running time of the composed MPC with a well-trained neural network.
no code implementations • 29 Dec 2021 • Gilbert Bahati, Marsalis Gibson, Alexandre Bayen
This work in progress considers reachability-based safety analysis in the domain of autonomous driving in multi-agent systems.
no code implementations • 13 May 2022 • Nicolas Kardous, Amaury Hayat, Sean T. McQuade, Xiaoqian Gong, Sydney Truong, Tinhinane Mezair, Paige Arnold, Ryan Delorenzo, Alexandre Bayen, Benedetto Piccoli
The choice of these parameters in the lane-change mechanism is critical to modeling traffic accurately, because different parameter values can lead to drastically different traffic behaviors.
no code implementations • 22 May 2022 • Fangyu Wu, Alexandre Bayen
Single-lane car-following is a fundamental task in autonomous driving.
1 code implementation • 19 Sep 2022 • Fangyu Wu, Dequan Wang, Minjune Hwang, Chenhui Hao, Jiawei Lu, Jiamu Zhang, Christopher Chou, Trevor Darrell, Alexandre Bayen
Decentralized multiagent planning has been an important field of research in robotics.
no code implementations • 14 Apr 2023 • Tianya Terry Zhang, Peter J. Jin, Sean T. McQuade, Alexandre Bayen, Ph. D., Benedetto Piccoli
Car-following (CF) algorithms are crucial components of traffic simulations and have been integrated into many production vehicles equipped with Advanced Driving Assistance Systems (ADAS).
no code implementations • 13 Sep 2023 • Derek Gloudemans, Gergely Zachár, Yanbing Wang, Junyi Ji, Matt Nice, Matt Bunting, William Barbour, Jonathan Sprinkle, Benedetto Piccoli, Maria Laura Delle Monache, Alexandre Bayen, Benjamin Seibold, Daniel B. Work
This work introduces a multi-camera tracking dataset consisting of 234 hours of video data recorded concurrently from 234 overlapping HD cameras covering a 4. 2 mile stretch of 8-10 lane interstate highway near Nashville, TN.