Robust multiagent reinforcement learning toward coordinated decision-making of automated vehicles
Automated driving is essential for developing and deploying intelligent transportation systems. However, unavoidable sensor noises or perception errors may cause an automated vehicle to adopt suboptimal driving policies or even lead to catastrophic failures. Additionally, the automated driving longi...
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Main Authors: | He, Xiangkun, Chen, Hao, Lv, Chen |
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Other Authors: | School of Mechanical and Aerospace Engineering |
Format: | Article |
Language: | English |
Published: |
2024
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/173497 |
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Institution: | Nanyang Technological University |
Language: | English |
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