In:
20th International Conference on Industrial Informatics, INDIN, IEEE, IEEE
Multi-Agent Deep Reinforcement Learning For Real-World Traffic Signal Controls - A Case Study
Jul 2022
Literatur Beschaffung:
20th International Conference on Industrial Informatics, INDIN, IEEE, IEEE
Bibtex: Download Bibtex
@inproceedings{Multi-Agent Deep Reinforcement Learning For Real-World Traffic Signal Controls - A Case Study,
}
| author | = | {Friesen, Maxim and Jasperneite, Jürgen and Tan, Tian and Wang, Jie}, |
| title | = | {Multi-Agent Deep Reinforcement Learning For Real-World Traffic Signal Controls - A Case Study}, |
| abstract | = | {}, |
| booktitle | = | {20th International Conference on Industrial Informatics, INDIN, IEEE}, |
| year | = | {2022}, |
| month | = | {Jul}, |
| publisher | = | {IEEE}, |
| address | = | {Online}, |
| editor | = | {}, |
| pages | = | {8}, |
| organisation | = | {}, |
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