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Autonomous driving holds promise for increased safety, optimized traffic management, and a new level of convenience in transportation.
T. M. Howard and A. Kelly, “Optimal rough terrain trajectory generation for wheeled mobile robots,” The International Journal of Robotics Research , vol. 26, no. 2, pp. 141–166, 2007
2007
Earlier work this paper cites.
P. Lucas and J. A. Ortega-Yagües, “Bertrand curves in the three-dimensional sphere,” Journal of geometry and physics , vol. 62, no. 9, pp. 1903–1914, 2012
2012
Earlier work this paper cites.
D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. Van Den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot et al. , “Mastering the game of go with deep neural networks and tree search,” nature , vol. 529, no. 7587, pp. 484–489, 2016
2016
Earlier work this paper cites.
D. Silver, J. Schrittwieser, K. Simonyan, I. Antonoglou, A. Huang, A. Guez, T. Hubert, L. Baker, M. Lai, A. Bolton et al. , “Mastering the game of go without human knowledge,” nature , vol. 550, no. 7676, pp. 354–359, 2017
2017
Earlier work this paper cites.
S. Liu, N. Atanasov, K. Mohta, and V. Kumar, “Search-based motion planning for quadrotors using linear quadratic minimum time control,” in 2017 IEEE/RSJ international conference on intelligent robots and systems (IROS) . IEEE, 2017, pp. 2872–2879
2017
Earlier work this paper cites.
2018
Earlier work this paper cites.
O. Vinyals, I. Babuschkin, W. M. Czarnecki, M. Mathieu, A. Dudzik, J. Chung, D. H. Choi, R. Powell, T. Ewalds, P. Georgiev et al. , “Grandmaster level in starcraft ii using multi-agent reinforcement learning,” Nature , vol. 575, no. 7782, pp. 350–354, 2019
2019
Earlier work this paper cites.
J. Schrittwieser, I. Antonoglou, T. Hubert, K. Simonyan, L. Sifre, S. Schmitt, A. Guez, E. Lockhart, D. Hassabis, T. Graepel, T. P. Lillicrap, and D. Silver, “Mastering atari, go, chess and shogi by planning with a learned model,” Nature , vol. 588, pp. 604 – 609, 2019. [Online]. Available: https://api.semanticscholar.org/CorpusID:208158225
2019
Cited alongside, same era.
S. Karimi and A. Vahidi, “Receding horizon motion planning for automated lane change and merge using monte carlo tree search and level-k game theory,” in 2020 American Control Conference (ACC) , 2020, pp. 1223–1228
2020
Cited alongside, same era.
2021
Cited alongside, same era.
S. Ozair, Y. Li, A. Razavi, I. Antonoglou, A. Van Den Oord, and O. Vinyals, “Vector quantized models for planning,” in international conference on machine learning . PMLR, 2021, pp. 8302–8313
L. Lei, R. Luo, R. Zheng, J. Wang, J. Zhang, C. Qiu, L. Ma, L. Jin, P. Zhang, and J. Chen, “Kb-tree: Learnable and continuous monte-carlo tree search for autonomous driving planning,” in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2021, pp. 4493–4500
2021
Later among the works it cites.
T. Hubert, J. Schrittwieser, I. Antonoglou, M. Barekatain, S. Schmitt, and D. Silver, “Learning and planning in complex action spaces,” in International Conference on Machine Learning . PMLR, 2021, pp. 4476–4486
2021
Later among the works it cites.
2021
Later among the works it cites.
Z.-H. Yin, W. Ye, Q. Chen, and Y. Gao, “Planning for sample efficient imitation learning,” 2022
2022
Later among the works it cites.
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2021
Cited alongside, same era.
I. Antonoglou, J. Schrittwieser, S. Ozair, T. K. Hubert, and D. Silver, “Planning in stochastic environments with a learned model,” in International Conference on Learning Representations , 2021
2021
Cited alongside, same era.
I. Danihelka, A. Guez, J. Schrittwieser, and D. Silver, “Policy improvement by planning with gumbel,” in International Conference on Learning Representations , 2021
2021
Cited alongside, same era.
W. Ye, S. Liu, T. Kurutach, P. Abbeel, and Y. Gao, “Mastering atari games with limited data,” Advances in Neural Information Processing Systems , vol. 34, pp. 25 476–25 488, 2021
2021
Cited alongside, same era.
2022
Later among the works it cites.
Z. Liu, S. Li, W. S. Lee, S. Yan, and Z. Xu, “Efficient offline policy optimization with a learned model,” 2023
2023
Closest in time.
L. Contributors, “LightZero: OpenDILab a lightweight and efficient toolkit designed for the mcts, alphazero, and muzero family of algorithms.” https://github.com/opendilab/LightZero, 2023
2023
Closest in time.