RLFTSim: Realistic and Controllable Multi-Agent Traffic Simulation via Reinforcement Learning Fine-Tuning

Fuente: arXiv

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Bibliographic Details
Main Authors:	Ahmadi, Ehsan, Schofield, Hunter, Khamidehi, Behzad, Arasteh, Fazel, Shan, Jinjun, Mou, Lili, Bai, Dongfeng, Rezaee, Kasra
Format:	Preprint
Published:	2026
Subjects:	Robotics Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning Multiagent Systems 68T40, 68T45, 68T42, 68T10, 68T07, 68T05, 68T37, 93A16 I.5; I.6; I.4; I.2; G.3; J.2
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2605.19033