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Multi-agent learning algorithms have been successful at generating superhuman planning in various games but have had limited impact on the design of deployed multi-agent planners.
Line generalisation by repeated elimination of points
M. Visvalingam and J. D. Whyatt · 1993
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Congested traffic states in empirical observations and microscopic simulations
Martin Treiber, Ansgar Hennecke, and Dirk Helbing · 2000
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Torcs, the open racing car simulator
Bernhard Wymann, Eric Espié, Christophe Guionneau, Christos Dimitrakakis, Rémi Coulom, and Andrew Sumner · 2000
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General lane-changing model mobil for car-following models
Arne Kesting, Martin Treiber, and Dirk Helbing · 2007
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Traffic simulation with aimsun
Jordi Casas, Jaime L Ferrer, David Garcia, Josep Perarnau, and Alex Torday · 2010
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Vehicle dynamics and control
Rajesh Rajamani · 2011
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Carla: An open urban driving simulator
Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, and Vladlen Koltun · 2017
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Beyond grand theft auto v for training, testing and enhancing deep learning in self driving cars
Mark Martinez, Chawin Sitawarin, Kevin Finch, Lennart Meincke, Alex Yablonski, and Alain Kornhauser · 2017
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Mastering the game of go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy P. Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel, and Demis Hassabis · 2017
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JAX: composable transformations of Python+NumPy programs, 2018
James Bradbury, Roy Frostig, Peter Hawkins, Matthew James Johnson, Chris Leary, Dougal Maclaurin, George Necula, Adam Paszke, Jake VanderPlas, Skye Wanderman-Milne, and Qiao Zhang · 2018
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Stable baselines
Ashley Hill, Antonin Raffin, Maximilian Ernestus, Adam Gleave, Anssi Kanervisto, Rene Traore, Prafulla Dhariwal, Christopher Hesse, Oleg Klimov, Alex Nichol, Matthias Plappert, Alec Radford, John Schulman, Szymon Sidor, and Yuhuai Wu · 2018
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Max Jaderberg, Wojciech M. Czarnecki, Iain Dunning, Luke Marris, Guy Lever, Antonio García Castañeda, Charles Beattie, Neil C. Rabinowitz, Ari S. Morcos, Avraham Ruderman, Nicolas Sonnerat, Tim Green, Louise Deason, Joel Z. Leibo, David Silver, Demis Hassabis, Koray Kavukcuoglu, and Thore Graepel · 2018
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An environment for autonomous driving decision-making, 2018
Edouard Leurent et al · 2018
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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
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Sim4cv: A photo-realistic simulator for computer vision applications
Matthias Müller, Vincent Casser, Jean Lahoud, Neil Smith, and Bernard Ghanem · 2018
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nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
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Summit: A simulator for urban driving in massive mixed traffic
Panpan Cai, Yiyuan Lee, Yuanfu Luo, and David Hsu · 2020
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Array programming with numpy
Charles R. Harris, K. Jarrod Millman, Stéfan van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, Robert Kern, Matti Picus, Stephan Hoyer, Marten H. van Kerkwijk, Matthew Brett, Allan Haldane, Jaime Fernández del Río, Mark Wiebe, Pearu Peterson, Pierre Gérard-Marchant, Kevin Sheppard, Tyler Reddy, Warren Weckesser, Hameer Abbasi, Christoph Gohlke, and Travis E. Oliphant · 2020
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Multi-agent connected autonomous driving using deep reinforcement learning
Praveen Palanisamy · 2020
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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
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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, Zoey Yang, Aurelien Chouard, Pei Sun, Jiquan Ngiam, Vijay Vasudevan, Alexander McCauley, Jonathon Shlens, and Dragomir Anguelov · 2021
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Intersim: Interactive traffic simulation via explicit relation modeling
Qiao Sun, Xin Huang, Brian C Williams, and Hang Zhao · 2022
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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
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Outracing champion gran turismo drivers with deep reinforcement learning
Peter R. Wurman, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik Subramanian, Thomas J. Walsh, Roberto Capobianco, Alisa Devlic, Franziska Eckert, Florian Fuchs, Leilani Gilpin, Piyush Khandelwal, Varun Kompella, HaoChih Lin, Patrick MacAlpine, Declan Oller, Takuma Seno, Craig Sherstan, Michael D. Thomure, Houmehr Aghabozorgi, Leon Barrett, Rory Douglas, Dion Whitehead, Peter Dürr, Peter Stone, Michael Spranger, and Hiroaki Kitano · 2022
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The surprising effectiveness of ppo in cooperative multi-agent games
Chao Yu, Akash Velu, Eugene Vinitsky, Jiaxuan Gao, Yu Wang, Alexandre Bayen, and Yi Wu · 2022
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Mastering the game of no-press diplomacy via human-regularized reinforcement learning and planning
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Parth Kothari, Christian Perone, Luca Bergamini, Alexandre Alahi, and Peter Ondruska · 2021
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Analysis of the generalized intelligent driver model (gidm) for uncontrolled intersections
Karsten Kreutz and Julian Eggert · 2021
Cited alongside, same era.
Isaac gym: High performance gpu-based physics simulation for robot learning
Viktor Makoviychuk, Lukasz Wawrzyniak, Yunrong Guo, Michelle Lu, Kier Storey, Miles Macklin, David Hoeller, Nikita Rudin, Arthur Allshire, Ankur Handa, et al · 2021
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Learning to fly—a gym environment with pybullet physics for reinforcement learning of multi-agent quadcopter control
Jacopo Panerati, Hehui Zheng, SiQi Zhou, James Xu, Amanda Prorok, and Angela P Schoellig · 2021
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Madras: Multi agent driving simulator
Anirban Santara, Sohan Rudra, Sree Aditya Buridi, Meha Kaushik, Abhishek Naik, Bharat Kaul, and Balaraman Ravindran · 2021
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Imagining the road ahead: Multi-agent trajectory prediction via differentiable simulation
Adam Ścibior, Vasileios Lioutas, Daniele Reda, Peyman Bateni, and Frank Wood · 2021
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Smarts: An open-source scalable multi-agent rl training school for autonomous driving
Ming Zhou, Jun Luo, Julian Villella, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, et al · 2021
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Vista 2.0: An open, data-driven simulator for multimodal sensing and policy learning for autonomous vehicles
Alexander Amini, Tsun-Hsuan Wang, Igor Gilitschenski, Wilko Schwarting, Zhijian Liu, Song Han, Sertac Karaman, and Daniela Rus · 2022
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Anton Bakhtin, David J. Wu, Adam Lerer, Jonathan Gray, Athul Paul Jacob, Gabriele Farina, Alexander H. Miller, and Noam Brown · 2023
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Adversarial diversity in hanabi
Brandon Cui, Andrei Lupu, Samuel Sokota, Hengyuan Hu, David J. Wu, and Jakob Nicolaus Foerster · 2023
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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
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Jaxmarl: Multi-agent rl environments in jax
Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Gardar Ingvarsson, Timon Willi, Akbir Khan, Christian Schroeder de Witt, Alexandra Souly, et al · 2023
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An extensible, data-oriented architecture for high-performance, many-world simulation
Brennan Shacklett, Luc Guy Rosenzweig, Zhiqiang Xie, Bidipta Sarkar, Andrew Szot, Erik Wijmans, Vladlen Koltun, Dhruv Batra, and Kayvon Fatahalian · 2023
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Bits: Bi-level imitation for traffic simulation
Danfei Xu, Yuxiao Chen, Boris Ivanovic, and Marco Pavone · 2023
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Pytorch 2: Faster machine learning through dynamic python bytecode transformation and graph compilation
Jason Ansel, Edward Z. Yang, Horace He, Natalia Gimelshein, Animesh Jain, Michael Voznesensky, Bin Bao, Peter Bell, David Berard, Evgeni Burovski, Geeta Chauhan, Anjali Chourdia, Will Constable, Alban Desmaison, Zachary DeVito, Elias Ellison, Will Feng, Jiong Gong, Michael Gschwind, Brian Hirsh, Sherlock Huang, Kshiteej Kalambarkar, Laurent Kirsch, Michael Lazos, Mario Lezcano, Yanbo Liang, Jason Liang, Yinghai Lu, C. K. Luk, Bert Maher, Yunjie Pan, Christian Puhrsch, Matthias Reso, Mark Saroufim, Marcos Yukio Siraichi, Helen Suk, Shunting Zhang, Michael Suo, Phil Tillet, Xu Zhao, Eikan Wang, Keren Zhou, Richard Zou, Xiaodong Wang, Ajit Mathews, William Wen, Gregory Chanan, Peng Wu, and Soumith Chintala · 2024
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Jumanji: a diverse suite of scalable reinforcement learning environments in jax, 2024
Clément Bonnet, Daniel Luo, Donal Byrne, Shikha Surana, Sasha Abramowitz, Paul Duckworth, Vincent Coyette, Laurence I. Midgley, Elshadai Tegegn, Tristan Kalloniatis, Omayma Mahjoub, Matthew Macfarlane, Andries P. Smit, Nathan Grinsztajn, Raphael Boige, Cemlyn N. Waters, Mohamed A. Mimouni, Ulrich A. Mbou Sob, Ruan de Kock, Siddarth Singh, Daniel Furelos-Blanco, Victor Le, Arnu Pretorius, and Alexandre Laterre · 2024
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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 · 2024
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Gigastep-one billion steps per second multi-agent reinforcement learning
Mathias Lechner, Tim Seyde, Tsun-Hsuan Johnson Wang, Wei Xiao, Ramin Hasani, Joshua Rountree, Daniela Rus, et al · 2024
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Pufferlib: Making reinforcement learning libraries and environments play nice
Joseph Suarez · 2024
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Gymnasium: A standard interface for reinforcement learning environments
Mark Towers, Ariel Kwiatkowski, Jordan Terry, John U Balis, Gianluca De Cola, Tristan Deleu, Manuel Goulão, Andreas Kallinteris, Markus Krimmel, Arjun KG, et al · 2024
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