Trends in Transfer Learning on Reinforcement Learning for Mobility Control
This paper provides an in-depth analysis of recent trends and advancements in applying Transfer Learning (TL) techniques to RL for vehicle control. We particularly focus on applications in autonomous driving and unmanned systems. The integration of TL with RL has demonstrated significant potential in overcoming key challenges such as Sim2Real transfer, multi-agent collaboration, and scalability in real-time applications.
Authors
- Lee Sung-Joon (ORCID: https://orcid.org/0009-0006-0713-8223)
- Soohyun Park (ORCID: https://orcid.org/0000-0002-5284-7188)
- Joongheon Kim (ORCID: https://orcid.org/0000-0002-1794-6076)
Institutions
- Korea University (KR)
- Sookmyung Women's University (KR)
Publication Details
- Published
- 2024-10-16
- DOI
- https://doi.org/10.1109/ictc62082.2024.10827089
- Citations
- 1
- Primary Topic
- Traffic control and management
- Type
- article
- Field-Weighted Citation Impact
- 0.33
Funders
- Ministry of Science and ICT, South Korea
- Institute for Information and Communications Technology Promotion