The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
CIRL: Controllable Imitative Reinforcement Learning for Vision-Based Self-driving
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Cites
Human-level control through deep reinforcement learning
Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., Graves, A., Riedmiller, M., Fidjeland, A. K., Ostrovski, G., et al. (2015) · Nature · doi:10.1038/nature14236 · Cited by 30,357
Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. G. (1998) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.1998.712192 · Cited by 27,225
Reinforcement Learning: An Introduction
(2005) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2004.842673 · Cited by 24,496
Continuous control with deep reinforcement learning
Lillicrap, T. P., Hunt, J. J., Pritzel, A., Heess, N., Erez, T., Tassa, Y., Silver, D., & Wierstra, D. (2015) · arXiv · doi:10.48550/arxiv.1509.02971 · Cited by 10,782
Asynchronous Methods for Deep Reinforcement Learning
Mnih, V., Badia, A. P., Mirza, M., Graves, A., Lillicrap, T. P., Harley, T., Silver, D., & Kavukcuoglu, K. (2016) · arXiv · doi:10.48550/arxiv.1602.01783 · Cited by 7,132
Introduction to Reinforcement Learning
Sutton, R. S., & Barto, A. G. (1998) · The MIT Press eBooks · Cited by 6,855
A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles
Paden, B., Cap, M., Yong, S. Z., Yershov, D., & Frazzoli, E. (2016) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2016.2578706 · Cited by 2,585
Generative adversarial imitation learning
Ho, J., & Ermon, S. (2016) · arXiv · doi:10.48550/arxiv.1606.03476 · Cited by 1,942
Deep Reinforcement Learning That Matters
Henderson, P., Islam, R., Bachman, P., Pineau, J., Precup, D., & Meger, D. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11694 · Cited by 1,685
Target-driven visual navigation in indoor scenes using deep reinforcement learning
Zhu, Y., Mottaghi, R., Kolve, E., Lim, J. J., Gupta, A., Fei-Fei, L., & Farhadi, A. (2017) · 2017 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra.2017.7989381 · Cited by 1,533
Cited by
ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst
Bansal, M., Krizhevsky, A., & Ogale, A. (2019) · Robotics: Science and Systems XV · doi:10.15607/rss.2019.xv.031 · Cited by 731
Multimodal end-to-end autonomous driving
Xiao, Y., Codevilla, F., Gurram, A., Urfalioglu, O., & Lopez, A. M. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2020.3013234 · Cited by 319
Learning to Rank Proposals for Object Detection
Tan, Z., Nie, X., Qian, Q., Li, N., & Li, H. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00836 · Cited by 56
Doan, Y. T.-T., Ho, M.-T., Nguyen, H.-K., & Han, H.-D. (2021) · Journal of Applied Phycology · doi:10.1007/s10811-021-02488-y · Cited by 20
Metadata
- Authors
- Liang, X., Wang, T., Yang, L., & Xing, E.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 604-620
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2837605352
- Cited by
- 285
- References
- 34
- FWCI
- 12.17
- Type
- conference paper
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: CIRL: Controllable Imitative Reinforcement Learning for Vision-Based Self-driving. https://app.cochat.ai/papers/10.1007/978-3-030-01234-2_36
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- Liang, X., Wang, T., Yang, L., & Xing, E. (2018). CIRL: Controllable Imitative Reinforcement Learning for Vision-Based Self-driving. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-01234-2_36
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
