Fetching the paper…
Reading the bibliography…
A central challenge for autonomous vehicles is coordinating with humans.
A mathematical theory of communication
Claude Elwood Shannon · 1948
Earlier work this paper cites.
Alvinn: An autonomous land vehicle in a neural network
Dean A Pomerleau · 1988
Earlier work this paper cites.
Algorithms for inverse reinforcement learning
Andrew Y Ng, Stuart Russell, et al · 2000
Earlier work this paper cites.
Congested traffic states in empirical observations and microscopic simulations
Martin Treiber, Ansgar Hennecke, and Dirk Helbing · 2000
Earlier work this paper cites.
General lane-changing model mobil for car-following models
Arne Kesting, Martin Treiber, and Dirk Helbing · 2007
Earlier work this paper cites.
Traffic simulation with aimsun
Jordi Casas, Jaime L Ferrer, David Garcia, Josep Perarnau, and Alex Torday · 2010
Earlier work this paper cites.
A reduction of imitation learning and structured prediction to no-regret online learning
Stéphane Ross, Geoffrey Gordon, and Drew Bagnell · 2011
Earlier work this paper cites.
End to end learning for self-driving cars
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, et al · 2016
Earlier work this paper cites.
Generative adversarial imitation learning
Jonathan Ho and Stefano Ermon · 2016
Earlier work this paper cites.
Mastering the game of go with deep neural networks and tree search
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, et al · 2016
Earlier work this paper cites.
End-to-end differentiable adversarial imitation learning
Nir Baram, Oron Anschel, Itai Caspi, and Shie Mannor · 2017
Earlier work this paper cites.
CARLA: An open urban driving simulator
Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, and Vladlen Koltun · 2017
Earlier work this paper cites.
Learning robust rewards with adversarial inverse reinforcement learning
Justin Fu, Katie Luo, and Sergey Levine · 2017
Earlier work this paper cites.
Virtual to real reinforcement learning for autonomous driving
Xinlei Pan, Yurong You, Ziyan Wang, and Cewu Lu · 2017
Earlier work this paper cites.
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
Earlier work this paper cites.
Deep q-learning from demonstrations
Todd Hester, Matej Vecerik, Olivier Pietquin, Marc Lanctot, Tom Schaul, Bilal Piot, Dan Horgan, John Quan, Andrew Sendonaris, Ian Osband, et al · 2018
Earlier work this paper cites.
Cirl: Controllable imitative reinforcement learning for vision-based self-driving
Xiaodan Liang, Tairui Wang, Luona Yang, and Eric Xing · 2018
Earlier work this paper cites.
Microscopic traffic simulation using sumo
Pablo Alvarez Lopez, Michael Behrisch, Laura Bieker-Walz, Jakob Erdmann, Yun-Pang Flötteröd, Robert Hilbrich, Leonhard Lücken, Johannes Rummel, Peter Wagner, and Evamarie Wießner · 2018
Cited alongside, same era.
A general reinforcement learning algorithm that masters chess, shogi, and go through self-play
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, et al · 2018
Cited alongside, same era.
Learning existing social conventions via observationally augmented self-play
Adam Lerer and Alexander Peysakhovich · 2019
Cited alongside, same era.
Grandmaster level in starcraft ii using multi-agent reinforcement learning
Oriol Vinyals, Igor Babuschkin, Wojciech M Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H Choi, Richard Powell, Timo Ewalds, Petko Georgiev, et al · 2019
Cited alongside, same era.
The hanabi challenge: A new frontier for ai research
Nolan Bard, Jakob N Foerster, Sarath Chandar, Neil Burch, Marc Lanctot, H Francis Song, Emilio Parisotto, Vincent Dumoulin, Subhodeep Moitra, Edward Hughes, et al · 2020
imitation: Clean imitation learning implementations
Adam Gleave, Mohammad Taufeeque, Juan Rocamonde, Erik Jenner, Steven H. Wang, Sam Toyer, Maximilian Ernestus, Nora Belrose, Scott Emmons, and Stuart Russell · 2022
Later among the works it cites.
Human-ai coordination via human-regularized search and learning
Hengyuan Hu, David J Wu, Adam Lerer, Jakob Foerster, and Noam Brown · 2022
Later among the works it cites.
Symphony: Learning realistic and diverse agents for autonomous driving simulation
Maximilian Igl, Daewoo Kim, Alex Kuefler, Paul Mougin, Punit Shah, Kyriacos Shiarlis, Dragomir Anguelov, Mark Palatucci, Brandyn White, and Shimon Whiteson · 2022
Later among the works it cites.
Modeling strong and human-like gameplay with kl-regularized search
Athul Paul Jacob, David J Wu, Gabriele Farina, Adam Lerer, Hengyuan Hu, Anton Bakhtin, Jacob Andreas, and Noam Brown · 2022
Later among the works it cites.
Metadrive: Composing diverse driving scenarios for generalizable reinforcement learning
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
“other-play” for zero-shot coordination
Hengyuan Hu, Adam Lerer, Alex Peysakhovich, and Jakob Foerster · 2020
Cited alongside, same era.
Deep learning for safe autonomous driving: Current challenges and future directions
Khan Muhammad, Amin Ullah, Jaime Lloret, Javier Del Ser, and Victor Hugo C de Albuquerque · 2020
Cited alongside, same era.
No-press diplomacy from scratch
Anton Bakhtin, David Wu, Adam Lerer, and Noam Brown · 2021
Cited alongside, same era.
nuplan: A closed-loop ml-based planning benchmark for autonomous vehicles
Holger Caesar, Juraj Kabzan, Kok Seang Tan, Whye Kit Fong, Eric Wolff, Alex Lang, Luke Fletcher, Oscar Beijbom, and Sammy Omari · 2021
Cited alongside, same era.
Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset
Scott Ettinger, Shuyang Cheng, Benjamin Caine, Chenxi Liu, Hang Zhao, Sabeek Pradhan, Yuning Chai, Ben Sapp, Charles R Qi, Yin Zhou, et al · 2021
Cited alongside, same era.
Off-belief learning
Hengyuan Hu, Adam Lerer, Brandon Cui, Luis Pineda, Noam Brown, and Jakob Foerster · 2021
Cited alongside, same era.
Analysis of the generalized intelligent driver model (gidm) for uncontrolled intersections
Karsten Kreutz and Julian Eggert · 2021
Cited alongside, same era.
Quanyi Li, Zhenghao Peng, Lan Feng, Qihang Zhang, Zhenghai Xue, and Bolei Zhou · 2022
Later among the works it cites.
Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world
Eugene Vinitsky, Nathan Lichtlé, Xiaomeng Yang, Brandon Amos, and Jakob Foerster · 2022
Later among the works it cites.
Diffusion policy: Visuomotor policy learning via action diffusion
Cheng Chi, Siyuan Feng, Yilun Du, Zhenjia Xu, Eric Cousineau, Benjamin Burchfiel, and Shuran Song · 2023
Later among the works it cites.
Waymax: An accelerated, data-driven simulator for large-scale autonomous driving research
Cole Gulino, Justin Fu, Wenjie Luo, George Tucker, Eli Bronstein, Yiren Lu, Jean Harb, Xinlei Pan, Yan Wang, Xiangyu Chen, et al · 2023
Later among the works it cites.
Reward (mis) design for autonomous driving
W Bradley Knox, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, and Peter Stone · 2023
Later among the works it cites.
Imitation is not enough: Robustifying imitation with reinforcement learning for challenging driving scenarios
Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Rebecca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, et al · 2023
Later among the works it cites.
Wayformer: Motion forecasting via simple & efficient attention networks
Nigamaa Nayakanti, Rami Al-Rfou, Aurick Zhou, Kratarth Goel, Khaled S Refaat, and Benjamin Sapp · 2023
Later among the works it cites.
Trajeglish: Learning the language of driving scenarios
Jonah Philion, Xue Bin Peng, and Sanja Fidler · 2023
Later among the works it cites.
Language conditioned traffic generation
Shuhan Tan, Boris Ivanovic, Xinshuo Weng, Marco Pavone, and Philipp Kraehenbuehl · 2023
Later among the works it cites.
Human-guided reinforcement learning with sim-to-real transfer for autonomous navigation
Jingda Wu, Yanxin Zhou, Haohan Yang, Zhiyu Huang, and Chen Lv · 2023
Later among the works it cites.
Bits: Bi-level imitation for traffic simulation
Danfei Xu, Yuxiao Chen, Boris Ivanovic, and Marco Pavone · 2023
Later among the works it cites.
Learning realistic traffic agents in closed-loop
Chris Zhang, James Tu, Lunjun Zhang, Kelvin Wong, Simon Suo, and Raquel Urtasun · 2023
Later among the works it cites.
The waymo open sim agents challenge
Nico Montali, John Lambert, Paul Mougin, Alex Kuefler, Nicholas Rhinehart, Michelle Li, Cole Gulino, Tristan Emrich, Zoey Yang, Shimon Whiteson, et al · 2024
Closest in time.