Inverse Reinforcement Learning to Enhance Physical Layer Security in 6G RIS-Assisted Connected Cars
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-53728-8_4
Reference11 articles.
1. Adams, S., Cody, T., Beling, P.A.: A survey of inverse reinforcement learning. Artif. Intell. Rev. 55(6), 4307–4346 (2022)
2. You, C., Lu, J., Filev, D., Tsiotras, P.: Advanced planning for autonomous vehicles using reinforcement learning and deep inverse reinforcement learning. Robot. Auton. Syst. 114, 1–18 (2019)
3. Kamboj, A.K., Jindal, P., Verma, P.: Machine learning-based physical layer security: techniques, open challenges, and applications. Wireless Netw. 27, 5351–5383 (2021)
4. Parras, J., Almodóvar, A., Apellániz, P.A., Zazo, S.: Inverse reinforcement learning: a new framework to mitigate an intelligent backoff attack. IEEE Internet Things J. 9(24), 24790–24799 (2022)
5. Tanveer, J., Haider, A., Ali, R., Kim, A.: Machine learning for physical layer in 5g and beyond wireless networks: a survey. Electronics 11(1), 121 (2021)
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